Data Science Analyst Jobs
Data Science Analyst jobs are open across technology, finance, healthcare, and retail, from entry-level to senior and lead roles, with specializations in predictive modeling, business intelligence, and machine learning engineering. Find a role that fits from the openings below and apply directly.
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Showing 5 of 580+ Data Science Analyst jobs
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 Analyst Jobs by Experience Level
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Find Data Science Analyst JobsData Science Analyst Job Market
Who's Hiring
- Amazon30
- Capital One23
- Meta15
- Information Technology Senior Management Forum12I
- Apple11
Top Industries Hiring
- Technology & Software68
- Retail27
- Education24
- Banking & Financial Services22
- Consulting & Professional Services19
What Employers Look For
The qualifications that appear most often in data science analyst jobs.
- Proficiency in Python or R for data analysis and statistical modeling
- Strong SQL skills for querying and manipulating large relational datasets
- Experience with data visualization tools such as Tableau or Power BI
- Bachelor's degree in statistics, computer science, mathematics, or a related field
- Familiarity with machine learning libraries such as scikit-learn or TensorFlow
- Experience communicating analytical findings clearly to non-technical stakeholders
Tips for Your Data Science Analyst Job Search
Quantify model impact on your resume
Recruiters for data science analyst roles want to see outcomes, not just tools. Replace 'built predictive models' with the business result: how much churn you reduced, revenue you influenced, or processing time you cut. Specific numbers make your resume stand out in applicant stacks.
Tailor your portfolio to the industry
A portfolio project in e-commerce demand forecasting won't land the same way at a hospital system. Swap or reframe one project to match the domain you're targeting. Hiring managers in healthcare or finance respond more to domain-relevant examples than technically impressive but unrelated work.
Filter openings by required stack, not just title
Data science analyst roles vary widely in their tooling. Some require Python and SQL, others center on Tableau or Power BI. Search by the specific tools listed in job descriptions you want to land, and deprioritize postings where your stack differs on more than two core requirements.
Apply early to roles that fit
Migrate Mate lists data science analyst openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a technical screen before the HR call
Many data science analyst pipelines front-load a take-home SQL or Python assessment before any recruiter conversation. Brush up on window functions, joins, and basic statistical concepts now, so you're not scrambling after you apply. Knowing this stage exists helps you pace your prep correctly.
Negotiate using role-specific comp levers
Data science analyst offers often include components beyond base salary: signing bonuses, equity, conference budgets, and learning stipends. When you receive an offer, ask explicitly about each. Employers who can't move on base often have flexibility on these secondary levers, especially at mid-size tech and fintech firms.
Data Science Analyst Jobs: Frequently Asked Questions
Which companies are hiring the most data science analysts?
The companies hiring the most data science analysts 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 especially active in technology, financial services, and healthcare sectors.
How many data science analyst jobs are remote?
About 64% of data science analyst openings are fully remote or hybrid as of August 2026, making it one of the more flexible roles in the analytics field. Positions focused on business intelligence, reporting, and predictive modeling tend to have the highest share of remote arrangements, while roles requiring close collaboration with lab or operations teams are more often on-site.
How do you become a data science analyst?
Start by building a foundation in statistics, Python or R, and SQL through coursework, bootcamps, or self-study. Develop a portfolio of projects that show you can clean messy data, build models, and communicate results. Earn a relevant degree or a recognized certification such as Google's Data Analytics Certificate or the IBM Data Science Professional Certificate. Then apply to entry-level analyst or junior data roles to gain professional experience.
Can you get a data science analyst job with little or no experience?
Yes, you can break into data science analyst roles without a formal work history by leading with a strong project portfolio. Build two or three end-to-end projects using publicly available datasets, publish them on GitHub, and explain your methodology clearly. Entry-level titles like junior data analyst, analytics associate, or business intelligence analyst are designed for candidates transitioning into the field, and many employers value demonstrated skill over years of experience.
What does the data science analyst interview process look like?
Most data science analyst pipelines follow four stages: an initial recruiter screen, a technical assessment covering SQL and Python or statistics, a case study or take-home project where you analyze a dataset and present findings, and a final round with the hiring manager and team. The technical screen and case study carry the most weight. Expect to explain your reasoning out loud, not just produce a correct answer.
Where can I find and apply to data science analyst jobs?
You can find and apply to data science analyst jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your skills, location preference, and experience level, then apply directly to each one that fits.
See All 580+ Data Science Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
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