data science manager

The Home Depot

Position Purpose: The Sr. Data Scientist is responsible for leading data science initiatives within the Pro Intelligence and Acquisition &amp; Integration space 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, Sr. 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: 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 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 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 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 Direct Manager/Direct Reports: This position reports to manager or above This position has 0 Direct Reports Travel Requirements: Typically requires overnight travel less than 10% of the time. Physical Requirements: 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. Working Conditions: Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: Must be eighteen years of age or older. Must be legally permitted to work in the United States. Preferred Qualifications: PhD in a quantitative field (Computer Science, Math, Statistics, etc.) 6+ years of experience in business intelligence and analytics Working knowledge of Microsoft Excel and Power Point Proficient in a modern scripting language (preferably Python) Proficient running queries against data (preferably with Google BigQuery or SQL) Proficient with data visualization software (preferably Tableau) Mastery utilizing statistical techniques to identify key insights that help solve business problems Proficient in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP Demonstrated proficiency in predictive modeling, data mining and data analysis Minimum Education: 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. Preferred Education: No additional education Minimum Years of Work Experience: 5 Preferred Years of Work Experience: No additional years of experience Minimum Leadership Experience: None Preferred Leadership Experience: None Certifications: None Competencies: Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals Collaborates: Building partnerships and working collaboratively with others to meet shared objectives Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences Cultivates Innovation: Creating new and better ways for the organization to be successful Customer Focus: Building strong customer relationships and delivering customer-centric solutions Develops Talent: Developing people to meet both their career goals and the organization's goals Directs Work: Provides direction, delegating and removing obstacles to get work done Drives Results: Consistently achieving results, even under tough circumstances Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels

Senior Data Scientist - Decision Analytics, Pro

Position Purpose: The Data Scientist will be a key architect in building next-generation agentic systems designed to revolutionize how professional customers manage complex projects. This role is responsible for developing autonomous AI capabilities that bridge the gap between simple search and sophisticated project quoting and fulfillment. You will leverage advanced techniques in Conversational AI, Retrieval-Augmented Generation (RAG), and Multimodal AI to unlock vast enterprise catalogs, automate project and product configuration, and provide real-time sourcing across a massive enterprise assortment. As a member of the team, you will design the reasoning paths that allow AI agents to navigate &quot;Pro-speak&quot; queries, extract intent from multimodal project inputs, and manage complex state across omnichannel sessions. Your work will directly empower Pro customers to move from discovery to optimized quoting to transaction in minutes, providing a seamless, self-serve experience at scale. Key Responsibilities: 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 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 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 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 Direct Manager/Direct Reports: This position typically reports to Manager or above This position has 0 Direct Reports Travel Requirements: Typically requires overnight travel less than 10% of the time. Physical Requirements: 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. Working Conditions: Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: Must be eighteen years of age or older. Must be legally permitted to work in the United States. Preferred Qualifications: Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience AI Orchestration: 4+ years of experience in Data Science with a focus on Conversational AI, GenAI, agentic workflows, custom tool-calling, and reasoning traces (e.g., LangSmith). Advanced Retrieval: Mastery of RAG and vector database architectures, specifically for extracting technical specs from unstructured enterprise data. Multimodal AI: Experience building pipelines to extract structured SKU-level intent from unstructured multimodal inputs, such as photos or handwritten lists. Algorithmic Logic: Background in similarity scoring and attribute-matching to resolve vague technical queries. State &amp; Engineering: Experience building stateful AI applications that maintain context across devices and sessions. Domain Expertise: Prior experience in B2B e-commerce, supply chain, or trade-related data is a significant plus. Technical Expertise: Experience in a modern scripting language (preferably Python); proficient running queries against data (preferably with Google BigQuery or SQL); proficient utilizing statistical techniques to identify key insights that help solve business problems; knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP; working knowledge of Microsoft Excel and Power Point Minimum Education: 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. Preferred Education: No additional education Minimum Years of Work Experience: 3 Preferred Years of Work Experience: No additional years of experience Minimum Leadership Experience: None Preferred Leadership Experience: None Certifications: None Competencies: Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals Collaborates: Building partnerships and working collaboratively with others to meet shared objectives Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences Customer Focus: Building strong customer relationships and delivering customer-centric solutions Drives Results: Consistently achieving results, even under tough circumstances Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels

Data Scientist

PETADATA

<div>
 Position: Technical Project Manager - Platform Solution Management team
 
 
 Location: GA (Hybrid)
 
 
 Experience: 10+ Years
 
 
 Work type: C2C
 
 
 Contract : 6 Months
 
 
 Visa Type: GC and US Citizen, H1B,H4-EAD
 
 
 Role Summary
 
 
 Technical Project Manager responsible for end-to-end delivery of complex enterprise solutions. Acts as a bridge between business and technology teams, driving product roadmap, execution, and stakeholder alignment in a Scaled Agile environment.
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Lead and manage large, complex enterprise projects
 </li>
 <li>
 Define and drive product and technology roadmap
 </li>
 <li>
 Plan and execute programs (scope, timeline, resources)
 </li>
 <li>
 Manage stakeholders across business and technology teams
 </li>
 <li>
 Drive Agile delivery (sprint planning, backlog, milestones)
 </li>
 <li>
 Identify and mitigate risks, issues, and dependencies
 </li>
 <li>
 Ensure successful project delivery within timelines and budgets
 </li>
 <li>
 Create and maintain project documentation and progress reports
 </li>
 <li>
 Collaborate with cross-functional teams and external partners
 </li>
 <li>
 Improve processes and project management practices
 </li>
 <li>
 Facilitate communication between business and IT teams
 
 
 </li>
 </ul>
 
 Required Skills
 
 
 
 <ul>
 <li>
 Technical Project / Program Management
 </li>
 <li>
 Agile / Scrum / SAFe (Scaled Agile)
 </li>
 <li>
 Stakeholder Management
 </li>
 <li>
 Cross-functional Collaboration
 </li>
 <li>
 Product Roadmap / Solution Delivery
 </li>
 <li>
 Risk &amp; Issue Management
 </li>
 <li>
 Resource Planning &amp; Allocation
 </li>
 <li>
 7+ years in Technical Project / Program Management
 </li>
 <li>
 Experience with complex development and integration projects
 </li>
 <li>
 Strong Agile delivery experience
 
 
 </li>
 </ul>
 Business &amp; Functional Skills
 
 
 <ul>
 <li>
 Business Analysis
 </li>
 <li>
 System Analysis
 </li>
 <li>
 Requirements Gathering
 </li>
 <li>
 Process Mapping &amp; Workflow Design
 </li>
 <li>
 Data Mapping
 </li>
 <li>
 Solution Design / Product Vision
 
 
 </li>
 </ul>
 Tools &amp; Technologies
 
 
 <ul>
 <li>
 Jira
 </li>
 <li>
 SQL
 </li>
 <li>
 Excel
 </li>
 <li>
 Miro / Lucidchart
 </li>
 <li>
 Visio
 </li>
 <li>
 Balsamiq
 </li>
 <li>
 Tableau
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 AWS Step Functions
 </li>
 <li>
 Camunda
 
 
 </li>
 </ul>
 
 Preferred Domain
 
 
 
 <ul>
 <li>
 Financial Services
 </li>
 <li>
 Asset Management
 </li>
 <li>
 Banking / Capital Markets
 
 
 </li>
 </ul>
 
 Educational Qualification
 
 
 
 Bachelor s or Master s degree in Computer Science or related field
 
 
 We offer a professional work environment and are given every opportunity to grow in the Information technology world.
 
 
 
 Note
 
 
 
 Candidates are required to attend Phone/Video Call / In-person interviews and after Selection of candidate (He/She) should go through all background checks on Education and Experience.
 
 
 Please email your resume to:divyam@petadata.ai
 
 
 Contact No: 510-279-6980
</div>

Technical Project Manager

Position Purpose: Decision Analytics associates produce insights that answer key enterprise questions around budget, priorities, courses of action, and important decisions. They develop frameworks for analysis by identifying the right metrics for consistent, effective insights that drive business outcomes. Decision Analytics associates are skilled in advanced analytics and analytical tools and languages such as GCP Big Query, Python, R, SQL, Jupyter Notebook, Adobe Analytics, and Tableau. While they may have the ability to support model development and AI/ML work, they are primarily focused on internal business insights (i.e., business intelligence). Decision Analytics associates possess the domain expertise to understand the businesses they support with their analysis. Senior Decision Analysts assist in the development of advanced analytics to support the company's strategic objectives. The role works cross-functionally with business partners from Merchandising, Finance, Operations, Supply Chain, Online and IT to design and implement decision analytics, tools, and new visibility/reporting capabilities. This role has responsibility for creating analytics, translating business questions to actionable insights, supporting ongoing analytical needs, designing new analytical tools, and collaborating with cross- functional teams to deliver high quality analytical solutions for The Home Depot. The Senior Decision Analyst monitors transformation of data and works with appropriate technology teams to resolve issues relating to incorrect mapping, business rules, and data deviations. This role is expected to leverage effective communication skills to translate complex analyses into understandable insights for business clients, internal teams and key decision makers. The role will be enabling scaling of AB testing platform so they must have that prior experience. Solid understanding of statistics and methodologies, familiarity with Central Limit Theorem and Hypothesis Testing is ideal (z-test, t-test, chi sq testing, ANOVA etc.,) The senior analyst will be regularly exploring new methods such as Non-Parametric Testing, bootstrap methods that elevate our platform. Explore new technical landscape in the world of Experimentation and bring it to the fold for Home Depot Key Responsibilities: 65% - Data Analytics - Analyzes large volumes of data and leverages data analytics tools to create new dashboards, reports and any additional ad-hoc requests, using a wide variety of database applications / analytical tools /languages including GCP BigQuery, SQL, SAS, R, Python, Jupyter Notebook, Adobe Analytics, and Tableau. 10% - Management of Data - Collaborate with other decision analysts to explore new sources of data; cleanse, validate and test data. 5% - Project Management &amp; Support - Supports end users, solve problems and troubleshoots numerous issues. 15% - Solution Development - Collaborate with stakeholders, business partners, colleagues, developers, and business analysts to deliver high quality analytics solutions. 5% - Technical Exploration &amp; Development - Develops additional technical competencies and subject matter expertise within core functional group, including but not limited to enhancements/modifications to systems and procedures. Direct Manager/Direct Reports: This position reports to the Manager This position has 0 direct reports Travel Requirements: No travel required. Physical Requirements: 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. Working Conditions: Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: Must be 18 years of age or older. Must be legally permitted to work in the United States. Preferred Qualifications: Master's degree in a quantitative field (Statistics, Analytics, Computer Science, etc.) or relevant work experience Understanding of the central limit theorem and hypothesis testing. 6+ years of experience in in data mining, statistical analysis, auditing, and/or forecasting Demonstrated expertise on data analysis and data visualization Demonstrated expertise on how to translate analysis into effective presentations Demonstrated expertise utilizing data analysis to identify key insights that help solve business problems Ability to apply experience in a wide variety of database applications, analytical tools and languages including SQL, SAS, Tableau, R, Python, Teradata, Oracle and similar tools Working knowledge of Microsoft Excel and Power Point Manage requests and roadmaps for insights for the online merchandising, marketing, and ELT organizations Produce deep, statistical analysis in service of predictive insights Ability to partner with requesting organizations to build KPI frameworks Ability to code in Python, R, SQL, Jupyter Notebook, VertexAI and AutoML Ability to visualize data using Tableau Experience managing multiple projects and working in a fast-paced environment Critical thinking skills to identify the strengths and weaknesses of alternative solutions; ability to understand and foresee implications of new information for current and future problems solving. Strong written and verbal communications skills. Ability to persuade, inform, and influence others based on findings. A track record of taking complex results and communicating them in an easily understood way. Superior interpersonal skills and ability to collaborate actively and work in a team environment. Ability to quickly learn and adapt to new technologies, tools, and techniques. Minimum Education: 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. Preferred Education: The knowledge, skills and abilities typically acquired through the completion of a master's degree program or equivalent degree in a field of study related to the job. Minimum Years of Work Experience: 5 Preferred Years of Work Experience: 6 Minimum Leadership Experience: No previous leadership experience Preferred Leadership Experience: No previous leadership experience Certifications: None Competencies: Action Oriented Collaborates Drives Engagement Communicates Effectively Customer Focus Drives Results Manages Conflict

Sr. Decision Analyst, Experimentation

Cushman & Wakefield

<div>Job Title
Data Engineer
Job Description Summary
Key Objectives: 
 
Supports the development, optimization, and maintenance of Cushman &amp; Wakefield&rsquo;s commercial real estate (CRE) forecasting infrastructure across the Americas. This role is focused on engineering robust data pipelines, automating model workflows, and ensuring the integrity and scalability of forecasting systems. 
 
Operate as a self-sufficient data practitioner, capable of independently delivering data solutions or working side-by-side with technology teams to ensure alignment and production readiness of QIG capabilities on an iterative basis. 
 
Works closely with senior economists, analytics leads, and technical teams to deliver high-quality, production-ready data solutions that underpin the firm&rsquo;s House View and related analytical products.
Job Description
Time Series Data Engineering, Maintenance &amp; Automation (40%)<ul><li>Prototype, build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in forecasting models.</li><li>Ensure data integrity and consistency across all QIG&rsquo;s inputs and outputs through rigorous validation and quality control procedures. Design and enforce structured data interfaces and integration patterns to ensure consistent ingestion and interoperability across internal and external data sources.</li><li>Work closely with cross-functional partners to define, refine, and validate data quality rules, using both automated checks and hands-on analysis to ensure outputs meet analytical expectations.</li><li>Performs exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and identify anomalies or inconsistencies.</li><li>Partner with PRI (Property Research &amp; Intelligence), TDS (Technology Data Solutions), GIS (Geographic Information System) and forecasting team to ensure governance of time series data, as revisions to geography-based competitive sets can occur.</li><li>Collaborate with PRI, TDS/GIS and other QIG teams to integrate internal and external data sources into infrastructure deployed by QIG teams.</li><li>Ensure Global Think Tank, Americas Research and other stakeholders have access to relevant time series (and forecast) data via various tools and capabilities in coordination with QIG leads. Work iteratively with partners to refine data outputs, validate usability, and adjust underlying pipelines or transformations as needed to meet evolving analytical requirements.</li></ul>
Technical Support (40%)<ul><li>Create and maintain documentation of any synthetic data model architecture, data flows, and diagnostic procedures. Have strong grasp of field-level data lineage and traceability to support transparency, reproducibility, and downstream analytical confidence.</li><li>Partner with Head of Data Science &amp; Geospatial Analytics to build state-of-the-art, novel real estate dataset, with additional relevant data geospatially integrated (e.g., demographics, socioeconomic data, zoning or flood maps, climate or walk score information); produce detailed specifications that guide engineering implementation.</li><li>Develop internal documentation and process automation, and serve as expert on the integration, application and processing of internal data, 3rd party vendor data and other public data (e.g., Census TIGER, IPUMS) as appropriate with QIG leads.</li><li>Advise, integrate and execute normalization methods with internal and external partners, co-developing approaches with technology teams when necessary and validating outputs through hands-on implementation and analysis.</li><li>Identify new data use cases for proprietary data, ensure appropriate cleaning and normalization techniques so data can be used in statistical, econometric and other commercial analytics applications.</li></ul>
Infrastructure Enhancement &amp; Collaboration (20%)<ul><li>Contribute to evolution of the QIG data infrastructure by identifying opportunities for efficiency gains, automation, and scalability.</li><li>Support the integration of emerging technologies (e.g., ML/AI, advanced lakehouse patterns) into data workflows under guidance from senior team members through hands-on experimentation, prototyping, or coordination with TDS as needed.</li><li>Coordinate with TDS and PRI on internal data and technology initiatives; contributing hands-on development or feedback where appropriate to scale, optimize, and productionize solutions in support of QIG capabilities.</li><li>Serve as the key liaison for all external data dependencies; monitor the evolution of 3rd party data products and capabilities, assess their fit against QIG analytical requirements, and produce intake specifications when new sources are approved for integration. As needed, partner with technology teams to evaluate and integrate internally managed data sources.</li><li>When/where appropriate, maintain a living requirements register and change log that tracks open data engineering requests, their status in the TDS backlog, acceptance criteria, and QIG sign-off outcomes.</li></ul>
Requirements:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Data Engineering, Data Science, Computer Science, Statistics, or a related technical field. Advanced degree a plus.</li><li>5-7 years of experience in data engineering or a hybrid analytical/engineering role, preferably in a forecasting or analytics/production environment. Real estate experience a plus.</li><li>Strong proficiency in Python/R, SQL, Databricks, Delta Lake and data pipeline frameworks (e.g., medallion architecture).</li><li>Experience with time series data, econometric / data science modeling workflows, and automation tools.</li><li>Familiarity with cloud platforms (e.g., Azure, AWS) and version control systems.</li><li>Demonstrated ability to operate in a collaborative, cross-functional environment, contributing both independently and alongside engineering and analytical teams to deliver data solutions.</li><li>Comfort working in iterative development settings, balancing hands-on execution with stakeholder collaboration and continuous feedback.</li><li>Strong attention to detail and commitment to data quality.</li><li>Excellent documentation, communication, and stakeholder management skills; comfortable operating as the technical translator between analytical domain experts and data engineering teams (when appropriate).</li><li>Excellent documentation and communication skills for technical audiences. Ability to participate meaningfully in engineering discussions.</li><li>Exposure to geospatial data concepts and CRE or macroeconomic datasets.</li><li>Experience working with agile/scrum delivery models in a data and analytics context.</li></ul> 

Cushman &amp; Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements. 

The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate&rsquo;s experience and qualifications. 

The company will not pay less than minimum wage for this role. 

The compensation for the position is: $ 114,750.00 - $135,000.00
Cushman &amp; Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.
In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman &amp; Wakefield, please call the ADA line at 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.
INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Data Engineer

Capgemini

<div><div><div><div>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
<div><div><div><h2 class="jobSectionHeader">Job Location : Cary, NC (Onsite/Hybrid from Day 1)</h2>
</div></div><div></div><div><div><h2 class="jobSectionHeader">Job Description</h2>
</div><div>We are seeking an experienced Data Scientist to join our growing Analytics and AI team. This role is responsible for developing and deploying advanced Machine Learning, Artificial Intelligence, and Generative AI solutions that drive customer engagement, marketing effectiveness, revenue growth, and business outcomes. The ideal candidate will have a strong blend of technical expertise, business acumen, and stakeholder management experience, particularly within the insurance and/or financial services industry.
</div></div><div><div><h2 class="jobSectionHeader">Key Responsibilities</h2>
</div><div><ul><li>Own technical decisions, project outcomes, timelines, and production stability within assigned business domains.</li>
<li>Design, develop, train, and optimize machine learning and deep learning models for marketing, customer engagement, sales, and business analytics use cases.</li>
<li>Analyze complex datasets to identify trends, patterns, anomalies, and actionable insights that support business strategy and decision-making.</li>
<li>Develop statistical models, predictive analytics, and machine learning algorithms using Python and Azure cloud technologies.</li>
<li>Build, deploy, and support production-ready ML and GenAI solutions, including API-based, batch, and real-time inference applications.</li>
<li>Collaborate with business stakeholders, product teams, and cross-functional partners to identify opportunities and implement data-driven solutions.</li>
<li>Integrate AI and ML capabilities into business applications and workflows through APIs, SDKs, and microservices.</li>
<li>Create compelling visualizations, dashboards, reports, and presentations to communicate analytical findings and recommendations to senior leadership and business partners.</li>
<li>Apply MLOps best practices to ensure scalability, reliability, performance monitoring, and operational excellence of AI/ML solutions.</li>
<li>Optimize platform components leveraging cloud-native architectures, distributed computing, and efficient resource management practices.</li>
<li>Stay current with emerging trends, technologies, and best practices in Artificial Intelligence, Data Science, Machine Learning, and Generative AI.</li>
<li>Promote responsible AI practices, including data privacy, model governance, bias mitigation, and model monitoring.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Required Qualifications</h2>
</div><div><ul><li>Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field.</li>
<li>8+ years of experience in Data Science, Machine Learning, Artificial Intelligence, and/or AI/ML Engineering.</li>
<li>5+ years of experience in the Insurance and/or Financial Services industry with exposure to sales, marketing, customer engagement, or customer analytics.</li>
<li>Proven experience designing, deploying, and operating production Machine Learning and/or Generative AI solutions, including APIs, batch processing, and real-time inference.</li>
<li>Strong experience developing Machine Learning models using Python, preferably in cloud environments.</li>
<li>Experience with Azure Machine Learning, Domino Data Lab, Power BI, or similar analytics and ML platforms.</li>
<li>Strong SQL skills and hands-on experience with data analysis, anomaly detection, data validation, and Exploratory Data Analysis (EDA).</li>
<li>Solid understanding of statistics, mathematics, predictive modeling, machine learning algorithms, and data science methodologies.</li>
<li>Experience leveraging AI and predictive analytics to improve customer experience, communication strategies, revenue generation, marketing effectiveness, and other business outcomes.</li>
<li>Familiarity with responsible AI principles, including data privacy, bias mitigation, model explainability, governance, and monitoring.</li>
<li>Excellent written and verbal communication skills, including the ability to present insights effectively through storytelling, visualizations, and executive-level presentations.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader">Preferred Qualifications</h2>
</div><div><ul><li>Experience with Generative AI, Large Language Models (LLMs), and modern AI frameworks.</li>
<li>Experience implementing MLOps and model lifecycle management practices in cloud environments.</li>
<li>Knowledge of cloud-native architectures and scalable AI/ML deployment patterns.</li>
<li>Experience working within highly regulated environments such as Insurance or Financial Services.</li>
</ul></div></div></div>The base compensation range for this role in the posted location is: 85786- 97273
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul>Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
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Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</div></div></div></div>

Position Purpose: The Sr. Product Manager - Merchandising Solutions Pricing is responsible for assessing internal pricing application needs for Merchants and Pricing Managers and working cross-functionally with other product and data science teams to find the fastest way to achieve value around those needs. The role focuses on delivering business value by surfacing strategic pricing decision, improving workflow efficiencies, and driving sales and margin benefits. Within Merchandising Solutions, Sr. Product Managers work closely with teams of developers, designers, and business partners. They support the entire lifecycle of product development including collaboration with business partners and readouts across all levels of the organization. Importantly, the Sr. Product Manager, must be able to work at the strategic level (generating innovative ideas for growth, change management, roadmap planning) and at the tactical level (analyzing data, solving problems, being a force multiplier and leader of their balanced team). The Sr. Product Manager is often responsible for products that are higher-profile and/or that are larger in scope. Key Responsibilities: 50% Strategy &amp; Planning: Seeks to empathize with and understand the end user deeply and use that knowledge to determine the fastest path to deliver value Translates business goals and end user needs into product strategy; communicates direction and product priorities to the development team, other matrixed teams, and third-party partners Identifies goals, metrics and analytics to determine product value; continually makes recommendations and refinements to the product backlog based on learnings Manages and grooms the product backlog; makes future decisions based on the value that will be delivered Partners with Finance to understand financial needs and assist in the creation of business plans for new opportunities Monitors research as well as the competitive landscape to recommend the best solutions and ensure that products remain or become best in class Ensures that product directions balance both the user needs and business goals of driving sales, improving efficiency and enhancing customer satisfaction 20% Delivery &amp; Execution: Formulates, tests and refines assumptions and hypotheses through user research and testing Documents, reviews and ensures that all quality and change control standards are met Creates, prioritizes and accepts user stories; incorporate them into release planning Makes product decisions that drive value on a daily basis Identifies and considers pros, cons, issues, obstacles, dependencies and value associated with features and enhancements Participates in standups, iteration planning sessions, product demo, and retrospectives Condenses complex technical concepts into non-technical language for stakeholders 30% People: Fosters collaboration with team members (Engineering, UX, etc.) to drive value and identify and resolve impediments Acts as a proponent of modern software development practices Advocates for the end user and stakeholder by becoming associated with the product, empathizing with and understanding user needs Works with the product team to continuously assess progress, disseminate lessons learned, and understand next steps Manages cross functional team and stakeholder expectations to execute on product strategy and provides education to requestors to determine prioritization based on tangible benefits and/or user experience Guides more junior team members in strategy, alignment, analysis and execution tasks Participates in and contributes to learning activities around modern software design and development core practices (communities of practice) Participates in talent acquisition, development and retention activities in support of team Direct Manager/Direct Reports: Typically reports to the Product Management Manager or Sr. Manager. Travel Requirements: Typically requires overnight travel less than 10% of the time. Physical Requirements: 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. Working Conditions: Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable. Minimum Qualifications: Must be eighteen years of age or older. Must be legally permitted to work in the United States. Preferred Qualifications: 3-6 years of relevant work experience Experience working as a Product Manager in a modern software development based enterprise environment Experience with modern software development product management practices and agile methodologies, specifically the extreme programming (XP) principles of paired programming, test driven development, and continuous deployment Proficiency in working in a fast paced, fluid environment where priorities shift on a regular basis Proficiency in communicating with and influencing functional and technical team members at all levels in the organization Proficiency in working as part of a collaborative, cross-functional, modern software design and development team Proficiency using AI tools to accelerate discovery, prototyping, and technical decision-making Proficiency in creating, prioritizing and accepting user stories Proficiency in conducting user research and testing to understand needs Proficiency in identifying goals, metrics and analytics to measure product value Familiarity with how AI-assisted development is reshaping software delivery practices and can be embedded in customer facing tools Experience guiding more junior team members through Product Management fundamentals in a professional setting Minimum Education: 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. Preferred Education: No additional education Minimum Years of Work Experience: 3 Preferred Years of Work Experience: No additional years of experience Minimum Leadership Experience: None Preferred Leadership Experience: None Certifications: None Competencies: Balances Stakeholders: Anticipating and balancing the needs of multiple stakeholders Business Insight: Applying knowledge of business and the marketplace to advance the organization's goals Collaborates: Building partnerships and working collaboratively with others to meet shared objectives Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences Cultivates Innovation: Creating new and better ways for the organization to be successful Customer Focus: Building strong customer relationships and delivering customer-centric solutions Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action Interpersonal Savvy: Relating openly and comfortably with diverse groups of people Manages Complexity: Making sense of complex, high quantity and sometimes contradictory information to effectively solve problems Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder Organizational Savvy: Maneuvering comfortably through complex policy, process and people-related organizational dynamics Situational Adaptability: Adapting approach and demeanor in real time to match the shifting demands of different situations Empathy: Understands the needs of multiple stakeholders and is responsive in meeting their needs with the most optimal resolution

Sr. Product Manager - Merchandising Solutions Pricing

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