data scientist sr

Now Brewing Senior Data Scientist, Store Analytics #tobeapartner

In order to make an application, simply read through the following job description and make sure to attach relevant documents.

From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and its 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.

As a Senior Data Scientist, you will support store analytics at Starbucks, focused on store development and operations. In this role, you will contribute to and lead strategic initiatives to optimize Starbucks’ retail store growth and portfolio strategy.

You will use your background in data science to help build tools and data products that support partners and our business.

You will be confident in communicating with all levels of business partners. You will collaborate cross-functionally with data engineers, data scientists, and business experts to help Starbucks make better decisions by using data and analytics skills.

As a senior data scientist, you will

Lead the design and development of scalable data science solutions from the start to the finish by utilizing machine learning, and statistical analysis.

Build scalable processes for cleaning, aggregating, and loading data.

• Understand business initiatives, challenges, questions, concerns, or ideas, transforming them into successful data science solutions, and monitor data science metrics and KPIs.
• Mentor data analysts & data scientists on best practices, processes, frameworks, and KPIs.
• Contribute to project planning, and assist the team with estimations, timelines, and prioritization. Assist in developing the analytical roadmap, data, and technology strategy.

We’d Love To Hear From People With

• Education : BS+ with a concentration in a quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, Quantitative Social Science or similar discipline. Masters preferred.
• Minimum of 5+ years of industry experience in data and analytics work.
• Strong problem-solving skills with the ability to influence leadership teams at different levels.
• Significant experience working with predictive and statistical modeling, machine learning, and strong expertise in all phases of the modeling pipeline.
• Strong SQL, databases, and ETL / ELT skills required including cleaning and managing data.
• Advanced competency and expertise in Python, R, or some combination.
• Experience working with distributed data processing frameworks such as Spark and Databricks, and languages such as Java, PySpark, or Scala.
• Strong collaboration instincts desire & ability to work with partners to achieve the best outcome for the business.
• Excellent communication, presentation, and storytelling skills. The role requires effective communication with colleagues, stakeholders, and leaders from diverse backgrounds.
• Proven ability to manage multiple, time-sensitive projects and competing priorities simultaneously to drive projects to completion with minimal guidance and high attention to details.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

We are committed to creating a diverse and welcoming workplace that includes partners with diverse backgrounds and experiences.

We believe that enables us to better meet our mission and values while serving customers throughout our global communities.

People of color, women, LGBTQIA+, veterans and persons with disabilities are encouraged to apply.

Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal state and local ordinances.

Starbucks Corporation 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 [email protected].

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