data science manager

The Home Depot

<div>Position Purpose:
Join our newly established Generative Business Intelligence (Gen BI) team and help shape the future of enterprise analytics. As a key player in this strategic initiative, you will partner closely with IT to build a foundational enterprise semantic layer and design advanced, multi-agent architectures. Your work will drive a curated, persona-based approach to Gen BI, empowering end-users across the organization with seamless access to actionable, AI-driven insights grounded in verified, trusted BI metrics. 
The Data Science Manager is responsible for leading a team of data scientists (individual contributors), ensuring that their efforts drive business profitability, increased efficiencies and improved customer experience. This role leads overall programs, maximizing resources, partnering with project teams and business partners, and supports problem solving efforts. Data Science Managers provide leadership, mentoring, and coaching to team members, along with supporting their development of business and technical skills . Based on the specific data science team, this role would need to be Proficient in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP. 
As a Data Science Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science solutions. This role is expected to collaborate with other Data Science Managers across the organization for aligning strategies and effectively managing talent. These responsibilities require effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations. 
Key Responsibilities:<ul><li>
40% People Management &amp; Team Leadership - Provide leadership, mentorship and coaching to Data Scientists (individual contributors) and evaluate performance, execution, and contribution; Attract, retain and develop top talent to build an effective and high performing team; Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress; Ensure appropriate processes and job-specific requirements are properly documented; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Manage resources effectively to align with strategic initiatives and business needs; Foster collaboration with team members to develop a supportive and engaged team; Support team in the design and development of algorithms and models to use against large datasets to create business insights; Drive team's results and celebrate accomplishments</li><li>
25% Project Management - Prioritize and assign projects by striking a balance between a variety of factors, like funding, return on investment, innovative or challenging work, among others; Manage programs for the team to ensure consistency of execution, balance of resources and quality solutions; Collaborate with program managers and business partners to align on objectives and expectations and ensure project teams deliver against them; Serve as escalation point for any issues or difficulties with specific projects; Provide executive updates to leaders at all levels of the organization on program effectiveness, team accomplishments, summary of findings and recommended solution, and explain internal and external impacts</li><li>
15% Strategy &amp; Business Development - Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills; Effectively develop trust and collaboration with internal customers and cross-functional teams; Ensure alignment with IT support model, collaboration, tools and governance to enable data scientists to be most effective in executing their roles; Collaborate with other data science managers across the organization to establish high level strategy and optimize talent management</li><li>
20% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Ensure best practices and vision for data analysis and model productionalization are leveraged</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position typically reports to Senior Manager or above</li><li>
This position has Direct Reports &amp; manages programs</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Strong background in Business Intelligence (BI), enterprise data strategy, and semantic layers.</li><li>
Experience building, deploying, or working with AI agents and multi-agent architectures.</li><li>
Hands-on experience with Databricks is a strong plus.</li><li>
9+ years of experience in business intelligence and analytics</li><li>
Previous people or project team management experience</li><li>
Expertise in predictive modeling, data mining and data analysis</li><li>
Mastery running queries against data (preferably with Google BigQuery or SQL)</li><li>
Proficient with data visualization software (preferably Tableau)</li><li>
Mastery utilizing statistical techniques to identify key insights that help solve business problems</li><li>
Proficient in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP</li><li>
Demonstrated proficiency in predictive modeling, data mining and data analysis</li><li>
Experience managing and growing team members in a professional setting</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
8</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals</li><li>
Builds Networks: Effectively building formal and informal relationship networks inside and outside the organization</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Engagement: Creating an environment where people are motivated to do their best to help the organization achieve its objectives</li><li>
Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action</li><li>
Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity</li><li>
Interpersonal Savvy: Relating openly and comfortably with diverse groups of people</li><li>
Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics</li><li>
Persuades: Using compelling arguments to gain the support and commitment of others</li><li>
Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies</li></ul></div>

Data Science Manager - GenBI

<div>Position Purpose:
The Data Science Sr. Manager - GenBI is responsible for leading a team of data scientists (individual contributors, technical experts, and/or people managers), ensuring that their efforts drive business profitability, increased efficiencies and improved customer experience. This role harmonizes between the continuous drive towards data science research and learning and the needs of the business. As a Data Science Sr. Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science solutions. This role is expected to lead the collaboration between Data Science Managers across the organization to align strategies and effectively manage talent. These responsibilities require effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations. 
As a Data Science Sr. Manager, you will provide executive summaries to all levels of the organization and leverage your business knowledge and network to identify opportunities to leverage data science solutions . This role is expected to lead collaboration between Data Science Managers across the organization for aligning strategies and effectively managing talent. These responsibilities require effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations. 
Key Responsibilities:<ul><li>
50% People Management &amp; Team Leadership - Provide leadership, mentorship and coaching to direct reports and evaluate performance, execution, and contribution; Support Data Science Director in establishing a clear vision for the team and influencing reach with business partners; Attract, retain and develop top talent to build an effective and high performing teams; Support team in development of business knowledge and technical skills with clear plans and regular assessment of progress; Develop onboarding and training plan for both technical and soft skills that will ensure high level of capabilities within the team; Foster collaboration and alignment between different data science roles to develop a supportive and engaged team; Ensure best practices and world-class techniques are leveraged in the solutioning for business problems and future team reach; Drive team's results and celebrate accomplishments</li><li>
15% Program Management - Prioritize and assign projects by striking a balance between a variety of factors, like funding, return on investment, innovative or challenging work, among others; Manage programs for the team to ensure consistency of execution, balance of resources and quality solutions; Collaborate with program managers and business partners to align on objectives and expectations and ensure project teams deliver against them; Serve as escalation point for any issues or difficulties with specific projects; Provide executive updates to leaders at all levels of the organization on program effectiveness, team accomplishments, summary of findings and recommended solution, and explain internal and external impacts; Be a champion and advocate for the team's capabilities, expertise, and needs</li><li>
25% Strategy &amp; Business Development - Leverage extensive business knowledge and relationships to seek out new business opportunities to leverage data science and advocate for team's skills; Effectively develop trust and collaboration with internal customers and cross-functional teams; Ensure alignment with IT support model, collaboration, tools and governance to enable data scientists to be most effective in executing their roles; Collaborate with other data science managers across the organization to lead the efforts of developing high level strategy and optimizing talent management</li><li>
10% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Ensure best practices and vision for data analysis and model productionalization are leveraged</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position reports to Director or above</li><li>
This position has Direct Reports and manages programs</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li><li>
Demonstrated proficiency in predictive modeling, data mining and data analysis</li><li>
Proficient managing and growing team members in a professional setting</li><li>
Proficiency in guiding more junior team members through Data Science fundamentals in a professional setting</li><li>
Demonstrated experience with translating high level strategy to tactical execution</li></ul> 
Preferred Qualifications:<ul><li>
11+ years of experience in business intelligence and analytics</li><li>
Previous people or project team management experience</li><li>
Demonstrated expertise in predictive modeling, data mining and data analysis</li><li>
Mastery running queries against data (preferably with Google BigQuery or SQL)</li><li>
Proficient with data visualization software (preferably Tableau)</li><li>
Mastery utilizing statistical techniques to identify key insights that help solve business problems</li><li>
Proficient in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
10</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals</li><li>
Builds Networks: Effectively building formal and informal relationship networks inside and outside the organization</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Engagement: Creating an environment where people are motivated to do their best to help the organization achieve its objectives</li><li>
Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action</li><li>
Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity</li><li>
Interpersonal Savvy: Relating openly and comfortably with diverse groups of people</li><li>
Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics</li><li>
Persuades: Using compelling arguments to gain the support and commitment of others</li><li>
Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies</li></ul></div>

Data Science Senior Manager - Generative BI

<div>Position Purpose:
The Sr. Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making. Sr. Data Scientists are expected to seek out business opportunities to leverage data science as a competitive advantage. Based on the specific data science team, this role would need to be Proficient in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.
 
As a Sr. Data Scientist, you will serve as a lead on data science projects, collaborating with project/product managers, providing prioritization of tasks, balancing workload and mentoring data scientists on the project team. This role is expected to present insights and recommendations to leaders and business partners and explain the benefits and impacts of the recommended solutions. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations. 
Key Responsibilities:<ul><li>
35% Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation</li><li>
30% Project Management &amp; Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team</li><li>
20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage</li><li>
15% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Define best practices and develop clear vision for data analysis and model productionalization; Contribute to library of reusable algorithms for future use, ensuring developed codes are documented</li></ul> 

Direct Manager/Direct Reports:<ul><li>
This position reports to manager or above</li><li>
This position has 0 Direct Reports</li></ul> 

Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 

Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 

Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 

Preferred Qualifications:<ul><li>
PhD in a quantitative field (Computer Science, Math, Statistics, etc.)
</li><li>6+ years of experience in business intelligence and analytics</li><li>
Working knowledge of Microsoft Excel and Power Point</li><li>
Proficient in a modern scripting language (preferably Python)</li><li>
Proficient running queries against data (preferably with Google BigQuery or SQL)</li><li>
Proficient with data visualization software (preferably Tableau)</li><li>
Mastery utilizing statistical techniques to identify key insights that help solve business problems</li><li>
Proficient in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP</li><li>
Demonstrated proficiency in predictive modeling, data mining and data analysis</li></ul> 

Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 

Preferred Education:<ul><li>
No additional education</li></ul> 

Minimum Years of Work Experience:<ul><li>
5</li></ul> 

Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 

Minimum Leadership Experience:<ul><li>
None</li></ul> 

Preferred Leadership Experience:<ul><li>
None</li></ul> 

Certifications:<ul><li>
None</li></ul> 

Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Cultivates Innovation: Creating new and better ways for the organization to be successful</li><li>
Customer Focus: Building strong customer relationships and delivering customer-centric solutions</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Results: Consistently achieving results, even under tough circumstances</li><li>
Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder</li><li>
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement</li><li>
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels</li></ul></div>

Sr Data Scientist - Supply Chain

<div>Position Purpose:
The Sr. Data Scientist is responsible for leading data science initiatives that drive business profitability, efficiencies and customer value by supporting the data science and analytical needs of THD&rsquo;s Cost Finance Team. This role assists in the development of the Home Depot advanced analytics, machine learning, and AI infrastructure that informs cost mitigation and strategic sourcing decisions. Sr. Data Scientists are expected to seek out business opportunities to leverage data science to improve the company&rsquo;s cost position and profitability. Based on the specific data science team, this role would need to be an expert in data science methods such as data engineering, pipeline development and maintenance, machine learning, and artificial intelligence as well as fluent in cost finance concepts.
As a Sr. Data Scientist, you will serve as a lead on data science projects, collaborating with finance managers and finance leadership, providing prioritization of tasks, balancing workload and mentoring data scientists on the project team. This role is expected to present insights and recommendations to leaders and business partners and explain the benefits and impacts of the recommended solutions. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships and partnerships, and leveraging business proficiency to solutions and recommendations. 
Key Responsibilities:<ul><li>
35% Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation</li><li>
30% Project Management &amp; Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team</li><li>
20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage</li><li>
15% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Define best practices and develop clear vision for data analysis and model productionalization; Contribute to library of reusable algorithms for future use, ensuring developed codes are documented</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position reports to manager or above</li><li>
This position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Master&rsquo;s Degree (Computer Science, Math, Statistics, etc.)</li><li>
Bachelor&rsquo;s Degree in required field (Mathematics, Statistics, Economics, Finance)</li><li>
6+ years of experience in business intelligence and data science</li><li>
Working knowledge of international trade dynamics and regulations or experience supporting retail cost mitigation efforts</li><li>
Demonstrated proficiency in predictive modeling, data mining and data analysis in a retail setting</li><li>
Experience developing production quality databases and pipelines for machine learning/artificial intelligence</li><li>
Demonstrated proficiency in building Gen AI agents and building agentic AI systems</li><li>
Experience working with Application Programming Interfaces (APIs)</li><li>
Working knowledge of Microsoft Excel and Power Point</li><li>
Proficient in Python</li><li>
Proficient running queries against Google BigQuery</li><li>
Proficient with Tableau</li><li>
Mastery utilizing statistical techniques to identify key insights that help solve business problems (including hypothesis testing, regression, time series, machine learning, and deep learning)</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
5</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Cultivates Innovation: Creating new and better ways for the organization to be successful</li><li>
Customer Focus: Building strong customer relationships and delivering customer-centric solutions</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Directs Work: Provides direction, delegating and removing obstacles to get work done</li><li>
Drives Results: Consistently achieving results, even under tough circumstances</li><li>
Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder</li><li>
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement</li><li>
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels</li></ul></div>

Senior Data Scientist - Generative BI

<div>Position Purpose:
The AI Strategy &amp; Transformation Lead is responsible for driving execution of the Enterprise &ldquo;Project Orion&rdquo; strategy, including Enterprise Data Products, GenBI, and Semantic / Intelligence Layers, while supporting and accelerating AI adoption within the Decision Analytics organization. This role acts as a horizontal integrator and operator, ensuring work across teams is aligned, clearly articulated, and tied to business value. In addition to the Project Orion focus, this role is expected to help accelerate organizational impact by building programs that upskill the organization, capture and celebrate value, and create a single, cohesive view of priorities across the organization.
The successful candidate will possess a deep working knowledge of Data Science, including an understanding of GenBI and AI applications and agentic workflows, along with a passion for technology, analytics, communication, and cross‑functional collaboration. 
Key Responsibilities:<ul><li>
60% Collaborate with stakeholders, business partners, colleagues, developers, and business analysts to deliver high quality analytics solutions</li><li>
25% Data analytics with large volumes of data, using a wide variety of database applications / analytical tools including SQL, SAS, R, and python</li><li>
5% Data cleansing, validation, testing</li><li>
5% Enhancements / modifications to systems &amp; procedures</li><li>
5% Supporting end users, problem solving, troubleshooting</li></ul> 
Direct Manager/Direct Reports:<ul><li>
Reports to a Director.</li><li>
This position has 0 direct reports.</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
8+ years working in Data Science and Analytics or consulting in similar spaces with a strong working and/or applied knowledge in Data Science, Analytics, AI (GenBI) or similar</li><li>
Strong business acumen, experience in Retail is a strong plus and ability to assess business impacts &amp; value</li><li>
Proven ability to work autonomously &amp; create value in an unstructured &amp; evolving role</li><li>
Proven ability to distill complex concepts for executive audiences</li><li>
Proven ability to manage &amp; influence without authority</li><li>
Proven ability to build &amp; execute on complex, cross-functional roadmaps</li><li>
Excellent verbal and written communication skills; including a passion for PowerPoint / storytelling</li><li>
Passion for Data Science &amp; Analytics and AI</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
6</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
None</li></ul></div>

Sr. Manager, Decision Analytics - AI Strategy & Transformation

The Coca-Cola Company

<div>The Coca Cola Company is transforming how its North America Supply Chain operates, using digital products to enable a supply chain that moves at the speed of the market. Our work connects planning, sourcing, manufacturing, and fulfillment into a responsive, reliable, and continuously improving network&mdash;one that can adapt quickly to change while operating at global scale.
Our product organization is built on small, empowered teams that move with clarity and purpose, making digital a true source of competitive advantage. Data and Analytics are a core partner to Product, Engineering and Design - shaping how decisions are made and value is delivered through insight, experimentation, and measurement. If you&rsquo;re excited to help build this practice and define from the ground up, we&rsquo;d love to meet you.
About the Role
The Head of Product Data &amp; Analytics, Supply Chain Digital Enablement (North America) leads the data discipline within the Product organization, overseeing the analysts and data scientists embedded in empowered product teams. This leader is responsible for how teams use data to understand behavior, measure progress, experiment confidently, and discover new opportunities.
You will build and scale a modern product insights capability that brings together analytics, data science, experimentation, instrumentation, and decision support. You will ensure teams move from opinion-driven to evidence-informed, while partnering closely with Design and Research to connect what users do with why they do it.
This role is deeply cross-functional. You will work alongside Product, Design, and Engineering leaders to define metrics, build measurement frameworks, instrument features, run experiments, and develop models that create both internal insight and customer-facing value.
Responsibilities
Build and lead the Data &amp; Analytics practice<ul><li>
Hire, develop, and lead analysts, data scientists, and experimentation specialists embedded in product teams</li><li>
Define roles, standards, and career paths for analytics and data science</li><li>
Create a culture rooted in curiosity, rigor, and clear storytelling</li></ul>
Make data foundational to product discovery and delivery<ul><li>
Ensure teams use data to understand behavior, measure outcomes, and evaluate ideas</li><li>
Guide the use of experiments, prototypes, and causal analysis to reduce risk</li><li>
Enable product leaders to shift from feature roadmaps to outcome-based KPIs and scorecards</li></ul>
Define measurement, instrumentation, and experimentation<ul><li>
Establish KPIs, guardrails, and leading indicators for each product area, including service levels, forecast accuracy, throughput, inventory health, and cost‑to‑serve</li><li>
Operationalize experimentation practices including A/B tests, holdouts, and causal inference</li><li>
Ensure products are instrumented correctly so teams are never &ldquo;flying blind&rdquo;</li></ul>
Lead core product analytics capabilities<ul><li>
Oversee user analytics, customer analytics, funnels, cohorts, and retention analyses</li><li>
Guide business and product economics analytics such as LTV, churn, and unit economics</li><li>
Ensure data quality, accuracy, and usability across platforms</li></ul>
Develop and apply data science for insight and customer value<ul><li>
Guide segmentation, forecasting, clustering, and propensity modeling</li><li>
Partner with product and engineering to embed predictive and adaptive models into product experiences</li><li>
Ensure ML models are monitored, evaluated, and continuously improved</li></ul>
Elevate data capability across the organization<ul><li>
Coach PMs, designers, and engineers to be confident, data-literate decision-makers</li><li>
Promote experimentation and analytics as routine parts of product work</li><li>
Scale learnings and insights across the organization to build shared knowledge</li></ul>
Influence product strategy and portfolio decisions<ul><li>
Size opportunities, prioritize bets, and guide investment decisions using data</li><li>
Provide scenario modeling and forecasting for portfolio sequencing</li><li>
Represent the data and insights perspective in senior forums</li></ul>
Key Qualifications<ul><li>
10+ years of experience in analytics, data science, or related fields, with at least five years leading teams in digital product environments</li><li>
Bachelor's degree in data science, statistics, economics, computer science, or related field</li><li>
Experience embedding analysts and/or data scientists within cross-functional product or engineering teams</li><li>
Strong foundation in product analytics including behavioral data, funnels, cohorts, and retention</li><li>
Deep experience with experimentation including A/B testing, test design, and interpretation</li><li>
Familiarity with data science techniques such as clustering, regression, propensity modeling, and recommendations</li><li>
Fluency with modern data platforms including warehouses, event tracking, BI tools, and experimentation frameworks</li><li>
Ability to translate complex analyses into clear, actionable insights for product and executive audiences</li><li>
Strong collaboration and influence skills across Product, Engineering, and Design</li></ul>
Preferred Qualifications<ul><li>
Advanced degree in data science, statistics, economics, computer science, or a related field preferred.</li><li>
Experience building or scaling data and analytics within empowered product team models</li><li>
Background applying causal inference or quasi-experimental methods in real-world environments</li><li>
Exposure to embedding ML models into customer-facing products</li><li>
Familiarity with AI and agentic systems as accelerators for analysis or modeling</li></ul>
Skills<ul><li>
Analytical rigor: Applies strong statistical and analytical judgment to define, measure, and interpret product outcomes with clarity and precision.</li><li>
Product and systems thinking: Connects data, behavior, and business goals; understands how metrics and models influence decisions across journeys, platforms, and teams.</li><li>
Experimentation expertise: Designs and governs experiments that produce reliable, decision-ready evidence and helps teams reduce risk and accelerate learning.</li><li>
Data science fluency: Guides analysts and data scientists in applying advanced techniques such as segmentation, forecasting, clustering, and recommendations to deliver insight and customer value.</li><li>
Insight storytelling and influence: Translates complex analyses into clear, compelling narratives that shape strategy, inform decisions, and align cross-functional stakeholders.</li><li>
Team leadership and capability building: Develops, coaches, and elevates analysts and data scientists; builds a culture of curiosity, rigor, and shared ownership of outcomes across product teams.</li></ul>
The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States.
Pay Range:
United States of America: $217,400 - $245,300
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
50
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Long-term Incentive Reference Value Percentage:
20
Long-term Incentive reference value is a market-based competitive value for your role.
Location(s):
United States of America
City/Cities:
Atlanta
Travel Required:
00% - 25%
Relocation Provided:
Yes
Job Posting End Date:
May 9, 2026
Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what&rsquo;s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors &ndash; curious, empowered, inclusive and agile &ndash; and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws. 
 
Pay Range:United States of America: $0 - $0 
Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered. 
 
Annual Incentive Reference Value Percentage:50 
Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target. 
 
Long-term Incentive Reference Value Percentage:20 
Long-term Incentive reference value is a market-based competitive value for your role.</div>

Head of Product Data & Analytics - Supply Chain Digital Enablement

<div>Position Purpose:
Supply Chain Economics owns the logic and data products that bridge supply chain operations with finance. This suite of datasets, analytics and models are key for financial processes, operational initiatives, merchant allocations and more. The team aims to continue to modernize its data products and provide insights into the costs and operational levers of The Home Depot's supply chain. The Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role applies industry-leading analytical methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP. 
As a Data Scientist, you will apply advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported. 
Key Responsibilities:<ul><li>
55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies</li><li>
20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation</li><li>
10% Business Collaboration - Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals</li><li>
15% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position typically reports to Manager or above</li><li>
This position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience</li><li>
4+ years of experience in business intelligence and analytics</li><li>
Working knowledge of Microsoft Excel and Power Point</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Proficient running queries against data (preferably with Google BigQuery or SQL)</li><li>
Proficient with data visualization software (preferably Tableau)</li><li>
Proficient utilizing statistical techniques to identify key insights that help solve business problems</li><li>
Knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP</li><li>
Demonstrated experience in predictive modeling, data mining and data analysis</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Customer Focus: Building strong customer relationships and delivering customer-centric solutions</li><li>
Drives Results: Consistently achieving results, even under tough circumstances</li><li>
Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder</li><li>
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement</li><li>
Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals</li><li>
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels</li></ul></div>

Data Scientist - Decision Analytics, Supply Chain Economics

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