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Data Scientist
Data Scientist
As a Data Scientist at Databricks, you will help foster a data-driven culture by tackling product and business challenges, while also serving as an internal customer to shape the future of Databricks products. Your responsibilities will include shaping key data science areas like segmentation and churn prediction, collaborating with cross-functional teams, and mentoring junior data scientists.
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 by solving product and business challenges. The Data team also acts as an in-house, production "customer" that rigorously tests Databricks products, influencing their future direction.
The Impact You Will Have
- Shape the direction of key data science areas such as segmentation, recommendation systems, forecasting, product analytics, and churn prediction and insights.
- Collaborate closely with Engineering, Product Management, Sales, and Customer Success to analyze product usage patterns and trends, making data-driven decisions, recommendations, and forecasts.
- Manage stakeholders within your focus area, gathering evolving requirements, defining project OKRs and milestones, and effectively communicating progress and results to non-technical audiences.
- Mentor and guide junior data scientists, assisting with project planning, technical decisions, and code and document reviews.
- Represent the data science discipline across the organization, advocating for a more data-driven approach.
- Develop self-serving internal data products to simplify data access and understanding within the company.
- Represent Databricks at academic and industrial conferences & events.
What We Look For
- 7+ years of experience in data science, machine learning, or advanced analytics in high-velocity, high-growth companies.
- Extensive experience in applying Data Science / ML for the end-to-end development and deployment of data-driven products to solve business problems.
- Familiarity with product data science, including understanding and tracking customer and user behavior through metrics like adoption, churn, cohorts, segmentation, and funnel analysis.
- Experience collaborating with and understanding the needs of stakeholders from various business functions, including Product, Sales, Engineering, Marketing, and Finance.
- Strong coding skills in general-purpose languages like Scala or Python, coupled with familiarity with software engineering principles such as 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 proficiency in SQL.
- MS or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering).