Staff Data Scientist

RDQ426R295

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.

Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products.

The impact you will have: 

• Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights.

• Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations and forecasts.

• Manage stakeholders for their focus area - gather changing requirements, define project OKRs and milestones, and communicate progress and results to a non-technical audience.

• 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

• Build self-serving internal data products to make data simple within the company.

• Represent Databricks at academic and industrial conferences & events.

What we look for:

3-8 bullets that describe what a person will have from their experience that will allow them to get to those outcomes listed above and that describe cultural or team competencies. Skills are important but so is team fit. Exclude “nice-to-haves” or “optional”.

• 7+ years of data science, machine learning, advanced analytics experience 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 for solving business problems.

• Familiarity with product data science - understanding and tracking customer and user behavior using lenses like adoption, churn, cohorts, segmentation and funnel analysis.

• Experience collaborating with and understanding the needs of stakeholders from a variety of business functions. We work most closely with Product, Sales and Engineering at the moment, but also work with the Marketing and Finance organizations.

• 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 proficiency in SQL.

• MS or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering)

 

Pay Range Transparency

Databricks is committed to fair and equitabl