Staff Data Scientist - Infrastructure

Databricks

P-57 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 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 work on top priorities for the company. The Data team also functions as an in-house, production "customer" that dog foods Databricks and drives the future direction of the products. The impact you will have: - “ Analysis at the speed of thought ”: Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists. - “ Extend capabilities of Databricks ”: Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product - “ Strategic business insights ”: 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. What we look for: - 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) 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. Based on the factors above, Databricks anticipates utilizing the full width of the range. 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 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 . 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 . Our Commitment to Diversity and Inclusion At Databricks, 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. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.