Staff Data Scientist

Key Skills

Data science techniques, Machine learning techniques, Python Programming, Scala Programming, SPARK Programming, SQL

Job Description

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. 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 fulfil 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 Staff Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping work on top priorities for the company. 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 key data science areas critical to Engineering driven efficient growth - customer retention, scalable product offerings, and an efficient and effective in-product / support experience.
• Work closely with Engineering, Technical Operations and Product stakeholders to understand customer pain points, and effectiveness of the in-product and support experience. Your insights will be used directly to make data-informed decisions on investments and priorities for Engineering.
• 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:

• 12+ 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
• Familiarity with applying data science to customer experience and customer facing operations - understanding customer and user behavior to measure experience, and outcomes (retention/churn, task completion, effort, etc.)
• Experience collaborating with and understanding the needs of stakeholders from a variety of business functions: Product, Engineering and Technical Operations
• Strong coding skills in general purpose languages like Scala or Python, and familiarity with software engineering principles around testing, code reviews and deployment
• Experience with distributed data processing systems like Spark, and proficiency in SQL

Benefits

• Benefits allowance
• Employee's Provident Fund
• Equity awards
• Gym reimbursement
• Annual personal development fund
• Work headphones reimbursement
• Business travel insurance
• Paid Parental Leave

About Databricks

Databricks is the data and AI company. More than 9,000 organizations worldwide — including Comcast, Condé Nast, and over 50% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe.