Location: WA-Seattle, USA
Company: Starbucks
Job Position: Data Scientist and Operations Analytics
JOB DESCRIPTION:
Qualification:
Education & Experience
BS+ with concentration in quantitative discipline - Stats, Math, Comp Sci, Engineering, Econ, Quantitative Social Science or similar discipline
- Minimum of 2+ years industry experience in data science
- Strong background working with predictive and statistical modeling, machine learning and strong expertise in all phases of the modeling pipeline
- Experience building complex data sets from multiple data sources, both internally and externally.
- Strong SQL, databases and ETL skills required including cleaning and managing data.
- Advanced competency and expertise in Python, R or some combination
- Ability to apply knowledge of multidisciplinary business principles and practices to achieve successful outcomes in cross-functional projects and activities
- Ability to educate others on statistical / machine learning methods
- Self-starter, attention to details and results orientated, able to work under minimal guidance.
- Proficient in communicating effectively with both technical and nontechnical stakeholders.
- Retail and eCommerce experience preferred
- Experience on Cloud platforms such as Azure, AWS, preferred
- Experience working with distributed data processing frameworks such as Spark and Data bricks, and languages such as Java, PySpark or Scala, preferred
Job Responsibility:
Use statistical, machine learning techniques to build models that address business needs.
- Extract data from various data sources; performs exploratory data analysis, cleanses, massages, and aggregates data
- Collaborate cross functionally with other data scientists, statisticians, and business analysts to define business problems and implement solutions.
- Employ scaling & automation to data preparation techniques
- Connect insights to business decision making options and next steps testing or research opportunities
- Understand business initiatives and serves as primary analytic resource in discussions with business partners to define business questions
- Drive creation of final insights package and recommendations; leads presentation
- Direct analytic component of implementation of insights into business processes and ensures appropriate testing takes place
- Develop project proposals, gains stakeholder buy-in, and ensures timelines are met
- Promote and advocate value of advanced analytics to solve business problems within department