Staff Data Scientist - Infrastructure
Leads data science initiatives to inform business decisions, generate strategic insights for engineering priorities, and build production ML tooling. Requires 7+ years experience, strong Python/SQL/Spark skills, and MS/PhD in quantitative field.
About the job
The impact you will have:
- “Analysis at the speed of thought”: Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists.
- “Extend capabilities of Databricks”: Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product.
- “Strategic business insights”: Lead insight generation for top company priorities, and key Engineering initiatives (reliability, and efficiency).
- Gather changing requirements, define project OKRs and milestones, and communicate progress and results to both technical and non-technical audiences.
- Mentor and guide junior data scientists on the team by helping with project planning, technical decisions, and code and document review.
- Represent the data science discipline throughout the organization, having a powerful voice to make us more data-driven.
- Represent Databricks at academic and industrial conferences & events.
What we look for:
- 7+ years of data science, machine learning, advanced analytics experience in high velocity, high-growth companies
- Extensive experience in applying Data Science / ML in production to build data-driven products for solving business problems.
- Experience collaborating with and understanding the needs of Senior level stakeholders from a variety of functions including: Engineering, Product, and Technical Operations.
- Ability to deal with ambiguity in fast paced environments by clarifying requirements and having a keen sense of 0 to 1 solutions.
- Adept at operating both as an individual contributor and identifying how to orchestrate the build through peers and investments in scalable tooling.
- Strong coding skills in Python and SQL
- Experience with distributed data processing systems like Spark and familiarity with software engineering principles around testing, code reviews and deployment.
- M.S. or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering)
Skills
Python, SQL, Spark, Machine Learning, Data Science, Distributed Data Processing, Software Engineering
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