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Data Scientist on the Data Team
Data Scientist on the Data Team
As a Data Scientist on the Data Team at Databricks, you will drive a data-driven culture by solving product and business challenges, and act as an internal customer to shape product development. Your responsibilities include shaping data science strategy, collaborating with stakeholders, mentoring team members, and building internal data products.
About the role
About the Role
As a Data Scientist on the Data Team at Databricks, you will play a crucial role in building a data-driven culture within the company by solving complex product and business challenges. The Data team also acts as an in-house, production "customer," dogfooding Databricks products and actively influencing their future direction.
The Impact You Will Have
- Shape the direction of key data science areas for 2020, including usage forecasting, product analytics, and user behavior and funnel analysis.
- Work closely with Product Management, Sales, Customer Success, and other stakeholders to understand product usage patterns and trends, making data-driven decisions and forecasts.
- Manage stakeholders for your focus area, gathering evolving requirements, defining project OKRs and milestones, and effectively communicating progress and results to non-technical audiences.
- Mentor and guide data scientists on the team by assisting with project planning, technical decisions, and code and document reviews.
- Build self-serving internal data products to simplify data accessibility within the company.
What We Look For
- Experience in applying Data Science / ML in production to build data-driven products for solving business problems.
- Familiarity with Product Analytics – understanding and tracking customer and user behavior using lenses like adoption, churn, cohorts, and funnel analysis.
- Experience collaborating with and understanding the needs of stakeholders from a variety of business functions, including Product, Customer Success, Engineering, Sales, Marketing, and Finance.
- Strong coding skills in general-purpose languages like Scala or Python, and familiarity with software engineering principles around testing, code reviews, and deployment.
- Proficient in data analysis and visualization using tools like R and Python.
- Experience with distributed data processing systems like Spark and Hadoop, and proficiency in SQL.
- BS/MS/PhD in Computer Science or a related field.