data scientist (Seattle, WA - U.S.) at Starbucks

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipelines, Pandas, Databricks SQL, Spark, Statistical Models, Predictive Models, Descriptive Models, Data Visualization, SQL, Python, PySpark, Geospatial Analytics, Operations Research, Linear Programming, Analytical Rigor, Communication Skills

Industry

Retail

Description

Build reusable data pipelines using tools such as Pandas, Databricks SQL, and Spark to uncover trends, prepare raw data for modeling, and generate actionable insights. Develop and Maintain Analytical Models - Design, enhance, and sustain statistical/analytical models tailored to specific domains such as store testing and experimentation, store development, supply chain, and marketing. Build Predictive and Descriptive Models - Leverage historical data, domain attributes, and external signals to develop models that address diverse business challenges and improve decision-making. Collaborate Cross-Functionally - Partner with teams across data engineering, operations, product, supply chain, and more to translate business needs into scalable data science solutions. 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. Proficiency in coding languages for data preparation and modeling, including SQL for querying large datasets and Python for building pipelines and statistical models Solid understanding of statistical concepts, and techniques, such as regression, classification, decision trees, clustering, and causal inference, with practical experience applying them to real-world problems Experience with data visualization tools and techniques (e.g., Tableau, Power BI) to communicate insights effectively to technical and non-technical audiences Demonstrated curiosity and analytical rigor, with a strong ability to explore complex datasets, identify patterns, and generate actionable insights Excellent attention to detail, along with strong written and verbal communication skills to collaborate across cross-functional teams and present findings to stakeholders Familiarity with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments and advanced analytical workflows Familiarity with geospatial analytics Familiarity with operations research and Linear Programming 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. You will also have access to backup care and DACA reimbursement. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. 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. We believe we do our best work when we're together, which is why we're onsite four days a week.

Responsibilities

Build reusable data pipelines and develop analytical models to generate actionable insights. Collaborate cross-functionally to translate business needs into scalable data science solutions.