Senior Decision Scientist, Customer Loyalty

Full time

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Employment Information

Job levelSenior level

Salary$119 700 - $211 600

IndustryRetail

Experience3+ years

LocationSeattle, WA, United States

Job Summary and Mission

This job contributes to Starbucks success by guiding data driven business decisions through leadership & analytics subject matter expertise to relevant business objectives. You will be able to design & recommend appropriate analytics approaches to solve key business problems, which can be developed in a cross-functional manner and can be consumed by business partners at all levels. There needs to be a focused attention on turning data into insights with modeling and acting in accordance with Starbucks guiding principles.

Summary of Key Responsibilities

Responsibilities and essential job functions include but are not limited to the following:

Analyze business requirements for Loyalty Marketing teams, and develop business cases & impact assessments of potential analytics solutions to support decisions in these teams
Actively consult with stakeholders to identify pain points in customer journey, ideate where analytics insights or data products may be useful, and co-create high-level solutions with a cross-functional working team.
Determine analytic approaches and statistical models to solve business problems; incorporate machine learning algorithms where appropriate.
Structure ambiguous problems collaborating with business SMEs and across the larger Analytics & Insights community to help design pragmatic data products (dashboards, data science models, ad-hoc analyses) that create tangible impact for business teams.
Influence adoption of insights to support data-driven decision-making
Communicate technical insights from analytics & data science projects to business partners at various levels in the organization that enables understanding and drives actionability.
Provide critical thinking and analytics subject matter expertise in stakeholder engagements
Lead discussions with business partners to define business questions and recommend appropriate methods to address business questions; translate unstructured strategic questions into structured analysis plan
Partner with larger A&I team, and technology to implement analytic insights and recommendations into business processes (e.g., automation of new KPIs, user acceptance testing for additional data feeds)
Extract data from various databases; perform exploratory data analyses, cleaning & aggregating insights. Employ scaling & automation to data preparation techniques
Introduce incremental improvements to data analysis, visualization, and presentation techniques to communicate discoveries
Research relevant emerging empirical methods and quantitative tools
Possess in-depth business knowledge to initiate and drive discussions with business partners to identify business issues needing analytic solutions
Establish brand and team as subject matter experts in advanced analytics across departments
Mentor junior decision scientists in pioneering techniques and business acumen

Summary of Experience

3 years experience within data analysis field or discipline

Basic Qualifications

Education: BA/BS w/ concentration in business or quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, or similar; Masters preferred

Required Knowledge, Skills and Abilities

Demonstrated experience with analytical methods, business process analysis & analytics enablement
High proficiency in developing key metrics for driving & maintaining healthy business performance
Strong problem-solving skills with ability to influence leadership teams at different levels
Working knowledge of data systems design & data technologies
knowledge of statistics & scripting (SQL, Python or R)
Ability to handle, and maintain the confidentiality of, highly sensitive information.
Demonstrated experience with communication tools (PowerPoint, virtual collaboration spaces)
Demonstrated experience with story telling techniques, and ability to communicate technical insights to a broad audience with different backgrounds
Business experience with several data visualization tools (e.g., Tableau)
Retail, customer loyalty, marketing or eCommerce experience preferred