Data Science Manager Jobs
Data Science Manager jobs are open across technology, finance, healthcare, and retail, at every level from senior individual contributor to principal and director, with specializations in machine learning, analytics engineering, and applied research. Find a role that fits from the openings below and apply directly.
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Now Brewing – director of data science – Coffeehouse Analytics! #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.
Join a transformative journey at the intersection of data, technology, and operations.
This strategic leadership role is pivotal in shaping how data science drives store development, staffing, deployment, experimentation, and market decisions across our coffeehouse network. You will lead multiple high-impact data science teams focused on building decision-support systems, optimization models, and experimentation frameworks that improve partner experience, operational efficiency, and business outcomes at scale.
As a director of data science, you will bring a strong product and people leadership mindset, balancing deep technical understanding with the ability to translate complex analytics into practical, actionable solutions. You will be a visible advocate for data science as a core capability for operational excellence and continuous improvement. This is a unique opportunity to lead a talented organization, influence enterprise decisions, and materially impact how Starbucks plans, operates, and learns.
As a director of data science – Coffeehouse Analytics, you will…
- Lead End-to-End Decision Science for Operations: Own data science strategy across staffing, scheduling, routing and deployment, market planning analytics, and coffeehouse testing—ensuring models and insights directly inform real-world decisions.
- Build and Scale High-Impact Teams: Lead, mentor, and grow multiple teams of data scientists and managers, fostering strong technical rigor, product thinking, and business partnership.
- Operational Planning & Optimization Leadership: Guide the development of predictive, optimization, and diagnostic models that support labor planning, capacity management, deployment tradeoffs, and network performance.
- Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn framework that enables rapid, trustworthy learning across coffeehouses and markets.
- Translate Analytics into Action: Partner closely with operations, finance, engineering, and field leaders to turn complex analytics into clear recommendations, tools, and decision frameworks.
- Influence Through Storytelling: Communicate insights, tradeoffs, and model outputs in compelling ways to senior leaders, helping shape strategy, prioritization, and investment decisions.
- Champion Adoption and Trust: Drive adoption of analytics products by ensuring they are usable, explainable, and embedded in operational workflows.
- Build Durable Data Science Products: Apply systems thinking to design scalable, reusable analytical products that move beyond one-off analyses and support long-term capability building.
- Strengthen Cross-Functional Collaboration: Work closely with data engineering, tools, and platform teams to ensure analytics solutions are production-ready, reliable, and extensible.
We’d love to hear from people with:
- Proven experience leading data science or advanced analytics teams, ideally supporting retail operations, store development, or labor.
- Strong background in applied analytics, including forecasting, optimization, experimentation, and decision-support systems.
- Experience building and scaling analytical products that are used in day-to-day business decision-making.
- In-depth experience with Python and reviewing production-quality analytical code.
- Ability to translate complex quantitative work into clear, actionable insights for executive and operational audiences.
- Strong cross-functional partnership and influencing skills, with a track record of driving outcomes through collaboration.
- Experience mentoring and developing data scientists and people leaders.
- Comfort operating in ambiguity and helping teams move from problem framing to scalable solutions.
- Experience driving the evolution from descriptive reporting to predictive and prescriptive decision support, including demand forecasting, capacity diagnostics, and optimization under real‑world constraints.
- Comfort balancing statistical rigor, AI innovation, and practical business constraints.
Join us and help shape the future of data-driven operations at Starbucks. Apply today!
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’s degree through Arizona State University’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.
- 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.
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.
Now Brewing – director of data science – Coffeehouse Analytics! #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.
Join a transformative journey at the intersection of data, technology, and operations.
This strategic leadership role is pivotal in shaping how data science drives store development, staffing, deployment, experimentation, and market decisions across our coffeehouse network. You will lead multiple high-impact data science teams focused on building decision-support systems, optimization models, and experimentation frameworks that improve partner experience, operational efficiency, and business outcomes at scale.
As a director of data science, you will bring a strong product and people leadership mindset, balancing deep technical understanding with the ability to translate complex analytics into practical, actionable solutions. You will be a visible advocate for data science as a core capability for operational excellence and continuous improvement. This is a unique opportunity to lead a talented organization, influence enterprise decisions, and materially impact how Starbucks plans, operates, and learns.
As a director of data science – Coffeehouse Analytics, you will…
- Lead End-to-End Decision Science for Operations: Own data science strategy across staffing, scheduling, routing and deployment, market planning analytics, and coffeehouse testing—ensuring models and insights directly inform real-world decisions.
- Build and Scale High-Impact Teams: Lead, mentor, and grow multiple teams of data scientists and managers, fostering strong technical rigor, product thinking, and business partnership.
- Operational Planning & Optimization Leadership: Guide the development of predictive, optimization, and diagnostic models that support labor planning, capacity management, deployment tradeoffs, and network performance.
- Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn framework that enables rapid, trustworthy learning across coffeehouses and markets.
- Translate Analytics into Action: Partner closely with operations, finance, engineering, and field leaders to turn complex analytics into clear recommendations, tools, and decision frameworks.
- Influence Through Storytelling: Communicate insights, tradeoffs, and model outputs in compelling ways to senior leaders, helping shape strategy, prioritization, and investment decisions.
- Champion Adoption and Trust: Drive adoption of analytics products by ensuring they are usable, explainable, and embedded in operational workflows.
- Build Durable Data Science Products: Apply systems thinking to design scalable, reusable analytical products that move beyond one-off analyses and support long-term capability building.
- Strengthen Cross-Functional Collaboration: Work closely with data engineering, tools, and platform teams to ensure analytics solutions are production-ready, reliable, and extensible.
We’d love to hear from people with:
- Proven experience leading data science or advanced analytics teams, ideally supporting retail operations, store development, or labor.
- Strong background in applied analytics, including forecasting, optimization, experimentation, and decision-support systems.
- Experience building and scaling analytical products that are used in day-to-day business decision-making.
- In-depth experience with Python and reviewing production-quality analytical code.
- Ability to translate complex quantitative work into clear, actionable insights for executive and operational audiences.
- Strong cross-functional partnership and influencing skills, with a track record of driving outcomes through collaboration.
- Experience mentoring and developing data scientists and people leaders.
- Comfort operating in ambiguity and helping teams move from problem framing to scalable solutions.
- Experience driving the evolution from descriptive reporting to predictive and prescriptive decision support, including demand forecasting, capacity diagnostics, and optimization under real‑world constraints.
- Comfort balancing statistical rigor, AI innovation, and practical business constraints.
Join us and help shape the future of data-driven operations at Starbucks. Apply today!
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’s degree through Arizona State University’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.
- 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.
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.
Data Science Manager Jobs by Experience Level
Top Cities Hiring Data Science Managers
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Find Data Science Manager JobsData Science Manager Job Market
Who's Hiring
- Amazon31
- Capital One23
- Meta15
- Information Technology Senior Management Forum12I
- Apple11
Top Industries Hiring
- Technology & Software69
- Retail28
- Education24
- Banking & Financial Services22
- Consulting & Professional Services19
What Employers Look For
The qualifications that appear most often in data science manager jobs.
- 5+ years of experience in data science or machine learning with at least 2 years managing a team
- Proficiency in Python or R and familiarity with SQL for data querying and analysis
- Experience deploying machine learning models in production environments at scale
- Ability to communicate data science findings clearly to non-technical executive stakeholders
- Experience working with cloud platforms such as AWS, GCP, or Azure
- Bachelor's or master's degree in statistics, computer science, mathematics, or a related quantitative field
Tips for Your Data Science Manager Job Search
Quantify your team leadership impact
Hiring managers for data science manager roles want to see how many data scientists you've managed, what projects you shipped, and what business outcomes resulted. Replace vague statements with numbers tied to team size, model performance, or revenue impact.
Tailor your resume to the stack
Many data science manager postings call out specific tools like Python, Spark, or dbt alongside cloud platforms. Mirror the exact tools named in each job description so your resume clears automated filters before a human ever reads it.
Apply early to roles that fit
Migrate Mate lists data science manager openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies with mature data teams
A data science manager role at a company with five data scientists is very different from one with fifty. Look for job descriptions that mention existing team structure, cross-functional partners, and data infrastructure, so you know what you're stepping into.
Prepare a technical leadership case study
Interviewers for data science manager roles routinely ask you to walk through a project end to end, covering how you set direction, unblocked your team, and communicated results to non-technical stakeholders. Prepare one detailed example before your first round.
Negotiate scope, not just compensation
When you get an offer, ask explicitly about team headcount, budget authority, and whether the role has input on hiring. These structural factors determine your ability to deliver, and they're often adjustable even when base compensation isn't.
Data Science Manager Jobs: Frequently Asked Questions
Which companies are hiring the most data science managers?
The companies hiring the most data science managers right now include Amazon, Capital One, and Meta, with the largest share of openings in California, New York, and Virginia, based on current listings on Migrate Mate as of August 2026. Demand is concentrated in technology, financial services, and healthcare organizations that have scaled their data teams in recent years.
How many data science manager jobs are remote?
About 64% of data science manager openings are fully remote or hybrid as of August 2026, reflecting strong employer flexibility for senior technical leadership roles. Sub-areas focused on analytics engineering and machine learning platform work tend to have the highest share of remote-friendly postings compared to roles tied to embedded product teams.
How do you become a data science manager?
You typically move into a data science manager role by first building deep technical credibility as a senior data scientist, then taking on informal leadership like mentoring junior teammates or owning a cross-functional project. From there, expressing interest in people management to your director, volunteering to lead a small team during a product launch, and demonstrating you can translate data work into business outcomes are the most direct paths to a formal manager title.
Can you get hired as a data science manager without prior management experience?
Yes, some companies hire strong senior individual contributors into their first data science manager role, especially at startups or in teams building out a new function. The strongest candidates without formal management history show they've led projects, mentored others, driven cross-functional alignment, and influenced decisions above their official level, which signals readiness to take on direct reports.
What does the data science manager interview process look like?
The data science manager interview process typically includes an initial recruiter screen, a hiring manager conversation focused on your leadership philosophy and team experience, a technical assessment covering modeling or analytical judgment, a case study or take-home project, and a final panel with cross-functional stakeholders such as product, engineering, or finance partners. Some companies add a separate session specifically on how you've handled underperformance or built team culture.
Where can I find and apply to data science manager jobs?
You can find and apply to data science manager jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and specialization, then apply directly to each listing from the page.
See All 581+ Data Science Manager Jobs
Find roles that match your experience and apply in just a few clicks.
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