Staff Data Scientist - Infrastructure

About the role

The Data Scientist on the Data Team at Databricks will play a crucial role in building a data-driven culture within the company. They will work on top priorities for the company, including building robust data science tooling for business leaders, analysts, and other data scientists, extending capabilities of Databricks, and leading insight generation for strategic business insights.

Responsibilities

• Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists.
• Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product.
• 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.

Requirements

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).

Qualifications

None specified.

Skills

None specified.

Benefits

Pay Range Transparency: Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Local Pay Range: $192,000—$260,000 USD

Company Overview

About Databricks: Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.

To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Company Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Equal Opportunity Employer

We are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.