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.
192k – 260k/yr
On-site7+ YOEData Science
About the role
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
PythonSQLSparkMachine LearningData ScienceDistributed Data ProcessingSoftware Engineering
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192k – 260k/yr
On-site7+ YOEData Science
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