Data Scientist II
Indexed description
What The Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business.
- Define how our teams measure success, by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing.
- Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
- Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, and optimization initiatives.
- 3+ years proven experience in product analytics or ontological data modeling.
- M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields.
- Advanced SQL and Python expertise.
- Basic understanding of experimental design (such as A/B experiments) and statistical methods.
- Ability and experience in extracting insights from data, and summarizing learnings / takeaways.
- Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar).
- Excellent judgment, critical-thinking, and decision-making skills.
- Balance attention to detail with swift execution.
- Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Machine Learning or other quantitative fields.
- 4+ years industry experience in consumer facing product analytics.
- Strong storytelling: distill interesting and hard-to-find insights into a compelling, concise data story.
- Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds.
- Ability to solve complex business problems that cross multiple product/project areas and teams.
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