decision scientist - Data & Analytics (Seattle,WA) at Starbucks

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Feb, 26

Salary

0.0

Posted On

07 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipelines, Data Visualization, SQL, Python, Statistical Concepts, Data Storytelling, Collaboration, Analytical Models, Predictive Models, Descriptive Models, Attention to Detail, Communication Skills, Pandas, Databricks, Spark, PySpark

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. Execute Analyses and Influence Strategic Decisions - Deliver complex analyses and translate results into actionable insights through clear reporting and data storytelling, providing recommendations that guide long-term business strategies. Collaborate Cross-Functionally - Partner with teams across data engineering, operations, product, supply chain, and more to translate business needs into scalable data science solutions. Contribute to Development and Maintenance of Analytical Models - work with the analytical team to design, enhance, and sustain statistical/analytical models tailored to specific domains such as store testing and experimentation, store development, supply chain, and marketing. Contribute to Predictive and Descriptive Models - Leverage historical data, domain attributes, and external signals to support the development of models that address diverse business challenges and enhance decision-making. 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 data visualization tools and techniques (e.g., Tableau, Power BI) to communicate insights effectively to technical and non-technical audiences 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 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 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 execute analyses to influence strategic decisions. Collaborate cross-functionally to translate business needs into scalable data science solutions.