machine learning manager

Gathern

<div>Job Purpose:
The Business Intelligence Manager owns the company&rsquo;s Business Intelligence function and is accountable for turning data into trusted insights that drive strategic and operational decisions. This role leads the activation of BI across the organization, focusing on correlation, causation, forecasting, and storytelling.The role also leads applied AI and machine learning initiatives, managing ML engineers to build, deploy, and operate production-grade, business-driven models, with clear ownership of applied MLOps practices to ensure reliability, scalability, and trust.
Key Responsibilities<ul><li>
 Lead the BI team in planning, developing, and delivering high-impact dashboards, reports, and analytics solutions</li><li>
 Business Intelligence Leadership</li></ul><ul><li>
Own the end-to-end Business Intelligence strategy and execution</li><li>
Establish BI as a core decision-support capability across the company</li><li>
Define and govern KPIs, metrics, and analytical standards</li><li>
Ensure insights consistently explain what happened, why it happened, and what to do next</li><li>
Lead executive and operational reporting and insight narratives</li></ul>
Analytics, Forecasting &amp; Insights<ul><li>
Oversee trend analysis, root-cause analysis, and correlation studies</li><li>
Drive forecasting, projections, and scenario analysis for planning and expectation-setting</li><li>
Ensure analytical outputs are explainable, assumption-driven, and decision-ready</li></ul>
Applied AI and Machine Learning Leadership<ul><li>
Lead and mentor ML engineers to design, build, and deploy applied machine learning models</li><li>
Own the applied ML and MLOps roadmap, aligned with BI and business priorities</li><li>
Guide the development of models such as:</li><li><ul><li>
Recommendation and pattern discovery models</li><li>
Anomaly detection</li></ul></li><li>
Define and enforce MLOps standards, including:</li><li>
Model versioning and lifecycle management</li><li>
Deployment and rollback strategies</li><li>
Monitoring model performance, drift, and data quality</li><li>
Retraining and validation processes</li><li>
Ensure ML models are:</li><li>
Business-driven and use-case oriented</li><li>
Explainable and interpretable</li><li>
Observable and maintainable in production</li><li>
Cross-Functional Leadership</li><li>
Act as the intelligence partner for Product, Finance, Operations, and Engineering</li><li>
Work closely with Data Engineering, Backend Engineering, and Platform teams to operationalize insights and ML models</li></ul>
Technical &amp; Analytical Requirements<ul><li>
Strong understanding of Business Intelligence and analytics practices</li><li>
Hands-on experience with BI tools (Power BI preferred)</li><li>
Strong analytical foundation, including:</li><li><ul><li>
Correlation vs causation</li><li>
Forecasting and scenario modeling</li><li>
Root-cause analysis</li></ul></li><li>
Solid understanding of data warehousing concepts (BigQuery preferred)</li><li>
Working knowledge of applied machine learning, including:</li><li><ul><li>
Supervised and unsupervised learning approaches</li><li>
Feature engineering and model evaluation</li><li>
Model explainability techniques</li></ul></li><li>
Working knowledge of MLOps concepts, including:</li><li><ul><li>
Model deployment and lifecycle management</li><li>
Monitoring for performance degradation and data drift</li><li>
Retraining strategies and validation workflows</li><li>
Collaboration with engineering teams on CI/CD and production readiness</li></ul></li><li>
Ability to guide ML engineers on both modeling and operationalization, without acting as a research data scientist</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field..</li><li>
5+ years of experience in business intelligence, data analytics, or data management.</li><li>
Applied ML models are deployed, monitored, and reliably operated in production</li><li>
MLOps practices ensure models remain accurate, observable, and trusted over time</li><li>
ML outputs are explainable and confidently used by business stakeholders</li><li>
BI remains the starting point for decisions, with ML and MLOps extending insight into action</li></ul></div>

BI Manager

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The Measurement Intelligence Science Team (MIST) in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. 
 
As an Applied Science Manager on the team, you will lead a team of scientists to define and execute a transformative vision for holistic measurement and reporting insights for ad effectiveness. Your team will own the science solutions for foundational experimentation platforms, foundational customer journey understanding technologies, state of the art attribution algorithms to measure the role of advertising in driving observed retail outcomes, and/or agentic AI solutions that help advertisers get quick access to custom insights that inform how to get the most out of their ad spend. 
 
Key job responsibilities 
You independently manage a team of scientists. You identify the needs of your team and effectively grow, hire, and promote scientists to maintain a high-performing team. 
You have a broad understanding of scientific techniques, several of which may fall out of your specific job function. 
You define the strategic vision for your team. You establish a roadmap and successfully deliver scientific solutions that execute that vision. 
You define clear goals for your team and effectively prioritize, balancing short-term needs and long-term value. 
You establish clear and effective metrics and scientific process to enforce consistent, high-quality artifact delivery. 
You proactively identify risks and bring them to the attention of your manager, customers, and stakeholders with plans for mitigation before they become roadblocks. You know when to escalate. 
You communicate ideas effectively, both verbally and in writing, to all types of audiences. You author strategic documentation for your team. You communicate issues and options with leaders in such a way that facilitates understanding and that leads to a decision. 
You work successfully with customers, leaders, and engineering teams. You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues. 
 
About the team 
We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>4+ years of applied research experience</li><li>3+ years of scientists or machine learning engineers management experience</li><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>Experience programming in Java, C++, Python or related language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li><li>PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Palo Alto - 211,400.00 - 286,000.00 USD annually 
USA, NY, New York - 202,200.00 - 273,600.00 USD annually</div>

Applied Science Manager, Ads Measurement Science

Information Technology Senior Management Forum

<div><div>Posted Date
5/07/2026
</div><div>Description
<div>Senior Manager, Data Science - Credit Review
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
In Capital One&rsquo;s Credit Review Models, Data and Innovative solutions team, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can&rsquo;t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners.
We partner with best-in-class data scientists, analysts, credit risk management experts, and engineers to innovate solutions that directly impact the company&rsquo;s bottom line in a meaningful way. We do it all in a collaborative environment that values individual insight, encourages each associate to take on new responsibilities, promotes continuous learning, and rewards innovation.
Role Description
In this role, you will:<ul><li>
Leverage a broad stack of technologies, such as, Python, Conda, AWS, H2O, Spark, and more, to reveal the insights hidden within huge volumes of numeric and textual data</li><li>
Build statistical and machine learning models to challenge the models in production</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals</li><li>
Partner with a cross-functional team of data scientists, credit risk experts, and product managers to deliver a product customers love</li></ul>
The Ideal Candidate is:<ul><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You&rsquo;re passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.</li><li>
Statistically-minded. You&rsquo;ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li></ul>
Basic Qualifications:<ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics</li><li>
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li></ul></li><li>
At least 2 years of experience leveraging open source programming languages for large scale data analysis</li><li>
At least 2 years of experience working with machine learning</li><li>
At least 2 years of experience utilizing relational databases</li></ul>
Preferred Qualifications:<ul><li>
PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics</li><li>
At least 1 year of experience working with AWS</li><li>
At least 5 years&rsquo; experience in Python, Scala, or R for large scale data analysis</li><li>
At least 5 years&rsquo; experience with machine learning</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Charlotte, NC: $209,000 - $238,500 for Sr Mgr, Data Science 

McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science 

Plano, TX: $209,000 - $238,500 for Sr Mgr, Data Science 

Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science 

Riverwoods, IL: $209,000 - $238,500 for Sr Mgr, Data Science 

Wilmington, DE: $209,000 - $238,500 for Sr Mgr, Data Science 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Manager, Data Science - Credit Review
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you&rsquo;ll be part of a team that&rsquo;s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
In Capital One&rsquo;s Credit Review Models, Data and Innovative solutions team, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We understand that we can&rsquo;t prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners.
We partner with best-in-class data scientists, analysts, credit risk management experts, and engineers to innovate solutions that directly impact the company&rsquo;s bottom line in a meaningful way. We do it all in a collaborative environment that values individual insight, encourages each associate to take on new responsibilities, promotes continuous learning, and rewards innovation.
Role Description
In this role, you will:<ul><li>
Leverage a broad stack of technologies, such as, Python, Conda, AWS, H2O, Spark, and more, to reveal the insights hidden within huge volumes of numeric and textual data</li><li>
Build statistical and machine learning models to challenge the models in production</li><li>
Flex your interpersonal skills to translate the complexity of your work into tangible business goals</li><li>
Partner with a cross-functional team of data scientists, credit risk experts, and product managers to deliver a product customers love</li></ul>
The Ideal Candidate is:<ul><li>
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You&rsquo;re passionate about talent development for your own team and beyond.</li><li>
Technical. You&rsquo;re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.</li><li>
Statistically-minded. You&rsquo;ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.</li><li>
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.</li><li>
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You&rsquo;re not afraid to share a new idea.</li></ul>
Basic Qualifications:<ul><li>
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:<ul><li>
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics</li><li>
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics</li><li>
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics</li></ul></li><li>
At least 2 years of experience leveraging open source programming languages for large scale data analysis</li><li>
At least 2 years of experience working with machine learning</li><li>
At least 2 years of experience utilizing relational databases</li></ul>
Preferred Qualifications:<ul><li>
PhD in &ldquo;STEM&rdquo; field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics</li><li>
At least 1 year of experience working with AWS</li><li>
At least 5 years&rsquo; experience in Python, Scala, or R for large scale data analysis</li><li>
At least 5 years&rsquo; experience with machine learning</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Charlotte, NC: $209,000 - $238,500 for Sr Mgr, Data Science 

McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science 

Plano, TX: $209,000 - $238,500 for Sr Mgr, Data Science 

Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science 

Riverwoods, IL: $209,000 - $238,500 for Sr Mgr, Data Science 

Wilmington, DE: $209,000 - $238,500 for Sr Mgr, Data Science 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>
</div><div>Salary
209,000.00 - 238,500.00 Annual
</div><div></div><div><div>Type<div>
Full-time</div></div></div></div>

Senior Manager, Data Science - Credit Review

Starbucks

<div>Now Brewing &ndash; Data Science Managers! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Data Science Manager, you&rsquo;ll lead a team of data scientists, decision scientists, and analysts to build models and apply advanced analytics to solve complex business problems. You&rsquo;ll coach partners in technical and career development, set standards and best practices, and ensure insights and machine learning solutions are scalable, measurable, and adopted into business workflows.
As a Data Science Manager, you will&hellip;<ul><li>
Lead and develop a high-performing team by coaching, creating development plans, and building a culture of strong execution, collaboration, and continuous learning.</li><li>
Drive end-to-end data science delivery from problem framing and data preparation through modeling, performance assessment, and operationalization of insights/models.</li><li>
Set and scale best practices across coding standards, version control, documentation, data security, and analytics/engineering practices&mdash;removing roadblocks and aligning cross-functional partners.</li></ul> 


We&rsquo;d love to hear from people with:<ul><li>
BA/BS (or equivalent experience)</li><li>
5&ndash;7+ years of experience in data science, analytics, or a closely related field</li><li>
Proficiency with Python or R, SQL, and relational databases</li><li>
Working knowledge of machine learning/statistical techniques (e.g., regression, decision trees, classification, causal inference, clustering)</li><li>
Experience with cloud data/analytics solutions (e.g., Azure or AWS)</li><li>
Experience managing and coaching a team, with strong written/verbal communication skills and attention to detail</li></ul> 
Preferred qualifications<ul><li>
MS in a quantitative field (e.g., Statistics, Math, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science) or equivalent advanced experience</li><li>
8+ years managing a small team (approximately 2&ndash;4 people) and developing technical talent</li><li>
Experience with production ML practices (shared codebases, package creation, repositories, SDLC best practices), plus distributed processing/modern platforms (e.g., Databricks or similar)</li><li>
Experience with hyperparameter tuning and ongoing model performance monitoring (measurement, drift, stability)</li></ul> 
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.<ul><li>If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.</li></ul>
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
We believe we do our best work when we're together, which is why we're onsite four days a week.
Join us and inspire with every cup. Apply today! 
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.</div>

senior manager, Data Science (Nashville, TN)

MA'ADEN

<div><div><div><div><div>Role Purpose:
The Data Science &amp; Analytics Manager is responsible for overseeing the end-to-end execution of data science and advanced analytics initiatives that support Maaden&rsquo;s operational and business objectives. The role ensures that data science projects are delivered with high quality, reliability, and measurable impact by managing workflows, coordinating cross-functional stakeholders, and maintaining strong alignment with enterprise data, AI, and governance standards.
As an operational leader, the Manager translates business needs into actionable analytical work, supervises the development of models, analytical products, and data pipelines, and ensures their successful deployment and adoption across functions. This role plays a critical part in embedding data-driven decision-making within production, maintenance, supply chain, engineering, and other business units by enabling teams to access trusted insights, robust analytical tools, and fit-for-purpose ML/AI solutions.
Through effective project management, quality oversight, and close collaboration with technical experts and business partners, the Data Science &amp; Analytics Manager helps accelerate Maaden&rsquo;s transition to a technology-enabled, AI-informed mining enterprise. 
1. Manage End‑to‑End Data Science Delivery
<ul><li>Oversee the development, implementation, and maintenance of databases and data collection systems.
</li><li>Manage the lifecycle of ML/AI initiatives&mdash;supporting problem framing, data exploration, feature engineering, model development, validation, and preparation for MLOps deployment.
</li><li>Ensure delivery of scalable, production‑ready models in alignment with enterprise data governance and AI standards.
</li><li>Conduct statistical analysis to interpret data insights and support decision‑making.
</li><li>Apply data mining techniques to uncover patterns, trends, and relationships in large datasets.
</li><li>Develop predictive models and machine learning algorithms to forecast future outcomes as required.
</li><li>Create clear data visualizations, dashboards, and reports to effectively communicate findings to business stakeholders.
</li><li>Collaborate with cross‑functional teams to understand business needs and translate them into data‑driven solutions.
</li><li>Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins.
</li><li>Stay updated on emerging techniques, tools, and technologies in data science and analytics.
</li><li>Promote experimentation, model versioning, automated retraining, and continuous improvement processes.
</li><li>Recommend enhancements to existing models and analytics workflows for greater efficiency and impact. 
</li></ul></div></div> 
<div><div>2. Data Operations
<ul><li>Partner with data engineering to design, operate, and maintain reliable data pipelines and analytical models, ensuring data accuracy, timeliness, and trustworthiness.
</li><li>Monitor data quality, resolve data issues, and enforce data best practices across teams.
</li><li>Support compliance with data security standards and relevant regulations
</li><li>Supervise the development and deployment of advanced ML models, predictive analytics, GenAI, and optimization solutions, consistent with responsibilities of analytics leadership roles.
</li><li>Ensure technical rigor across the end‑to‑end ML lifecycle: scoping data engineering modeling validation MLOps monitoring.
</li><li>Oversee production reliability, model drift management, and continuous improvement. 
</li></ul></div></div> 
<div><div>3. Team Leadership &amp; Capability Building
<ul><li>Manage and grow a multi‑disciplinary team (Lead Specialists, Senior Specialists, Data Scientists). Roles under this manager are explicitly listed in the org structure.
</li><li>Build technical excellence through coaching on ML, GenAI, statistics, feature engineering, and experimentation.
</li><li>Foster a culture of innovation, peer review, and reusable modeling frameworks. 
</li></ul></div></div> 
<div><div>4. AI Governance, Quality &amp; Standards
<ul><li>Steward high standards in model explainability, auditability, lineage, and risk management.
</li><li>Drive compliance with enterprise data governance, PDPL, and model‑risk principles referenced in internal DS/AI qualification guidance.
</li><li>Ensure adherence to Responsible AI requirements applicable to DS/AI roles (skills and qualifications guidance).
</li><li>Enforce data quality standards, lineage, and reproducibility across the team&rsquo;s projects.
</li><li>Support alignment with enterprise governance frameworks, including PDPL compliance.
</li></ul></div></div> 
</div></div>Minimum Qualifications, Experience and Competencies
Minimum Qualifications:
Bachelor&rsquo;s degree in computer science, Engineering, Data Science, Mathematics, Applied Mathematics, or Physics.
Minimum Experience:
<ul><li>10 &ndash; 12+ years&rsquo; experience in advanced analytics, ML/AI engineering, and industrial data science.
</li><li>Including at least 4 years leading or mentoring analytics professionals.
</li><li>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</li><li>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</li><li>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
</li><li>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS).
</li><li>Proven record of enabling cross-functional business impact through scalable, production-grade data science solutions.
</li></ul>Maaden High-Performance Competencies:
Core Competencies
<ul><li>Value realization from ML/analytics initiatives (impact delivered vs. target).
</li><li>On‑time delivery of analytics roadmap.
</li><li>Adoption rate and integration of solutions into business workflows.
</li><li>Model performance stability (drift incidents, uptime).
</li><li>Team capability maturity and talent development indicators. 
</li></ul>Skills:
<ul><li>Machine Learning &amp; AI Leadership
</li><li>Programming Expertise
</li><li>Generative AI Proficiency
</li><li>Strong Analytical &amp; Statistical Skills
</li><li>Business Strategy &amp; Product Thinking
</li><li>Ethics, Governance &amp; Responsible AI
</li><li>Leadership &amp; People Management</li></ul></div>

Manager, Data Science & Analytics

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
We are working on improving shopping on Amazon using the conversational capabilities of large language models and through customer behavioral data to make them more personalized for each customer. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. You&rsquo;ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you&rsquo;re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!<h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of scientists or machine learning engineers management experience</li><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>PhD in Computer Science, Computer Engineering, or related technical field; OR Master's Degree in Computer Science, Computer Engineering, or related technical field with 5+ years of experience as a Scientist/Engineer.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience building machine learning models or developing algorithms for business application</li><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Palo Alto - 211,400.00 - 286,000.00 USD annually 
USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually</div>

Applied Science Manager , Stores Foundation AI (SFAI)

QCC GH Petroleum

Head of AI &amp; Machine Learning | QCC GH PetroleumLocation: Muttrah Business Tower, Muscat, OmanSalary: OMR 4,000 per monthJob Type: Full-time / Executive LeadershipJob DescriptionQCC GH Petroleum is seeking a visionary Head of AI &amp; Machine Learning to spearhead our digital transformation and lead the integration of advanced intelligence into our refinery and upstream operations. Based in the prestigious Muttrah Business Tower, you will be responsible for defining the AI roadmap that optimizes production, enhances safety, and drives high-level predictive maintenance across our assets.As a senior leader, you will oversee a multi-disciplinary team of data scientists and engineers, translating complex petroleum engineering challenges into scalable AI solutions. With a highly competitive salary of OMR 4,000 per month, this role offers a unique opportunity to shape the future of energy in Oman through cutting-edge technology.Key Responsibilities<ul><li>Strategic Leadership: Define and execute the enterprise-wide AI/ML strategy, aligning technical initiatives with the commercial goals of QCC GH Petroleum.</li><li>Operational Optimization: Develop predictive models for refinery yield optimization, reservoir management, and equipment failure detection.</li><li>Team Building: Lead, mentor, and scale a high-performing team of AI researchers, ML engineers, and data analysts.</li><li>AI Governance: Establish frameworks for data ethics, model security, and governance to ensure the responsible deployment of AI in critical infrastructure.</li><li>Cross-Functional Collaboration: Partner with the Engineering and Operations departments to integrate AI insights into daily workflows at the Muttrah Business Tower and field sites.</li><li>Innovation: Stay at the forefront of Generative AI, Computer Vision, and Reinforcement Learning to maintain our competitive edge in the regional oil and gas market.</li></ul>Qualifications &amp; Requirements<ul><li>Education: PhD or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Petroleum Engineering (with a data focus), or a related field.</li><li>Experience: Minimum 10+ years in AI/ML, with at least 5 years in a leadership or executive capacity. Experience in the Energy or Industrial sector is highly advantageous.</li><li>Technical Mastery: Deep expertise in Python, TensorFlow/PyTorch, and cloud-native AI services (Azure/AWS).</li><li>Industry Knowledge: Familiarity with IoT sensors, SCADA systems, and industrial data pipelines.</li><li>Communication: Exceptional ability to present AI value propositions to C-suite executives and non-technical stakeholders.</li></ul>Benefits<ul><li>Tax-Free Salary: A premier monthly compensation of OMR 4,000.</li><li>Prime Location: Work from the heart of Muscat&rsquo;s business district in Muttrah.</li><li>Impact: Direct influence on the digital evolution of a growing petroleum leader in the GCC.</li><li>Relocation Support: Comprehensive package for international candidates (where applicable).</li></ul>How to ApplyAre you ready to lead the AI revolution in the petroleum industry? Submit your CV and a summary of your most significant AI implementations via Indeed today.الراتب المدفوع: ﷼٠٫٠٠٠&nbsp;لكل شهرموقع العمل: بشكل شخصي

Head of AI & Machine Learning

Search 10000+ Machine learning manager jobs near you this May. New roles added regularly across leading industries. Apply today.