RDQ427R169

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations.

Databricks is looking for a Principal Data Scientist to serve as the statistical voice of the Data Science organization. This person will make Databricks smarter and more data-driven at the highest levels of leadership — translating the full power of data science into clear, actionable narratives for our CEO, C-suite, and Board of Directors.

Our vision is simple: data drives every Databricks decision and action. To get there, we need a world-class statistician and communicator — someone who can bridge the gap between deep analytical rigor and executive decision-making. This is a pure IC role with company-wide influence: no direct reports, maximum leverage.

Databricks was founded in 2013 by the original creators of Apache Spark, Delta Lake, and MLflow. We built the Databricks Data Intelligence Platform to help organizations unify their data, analytics, and AI workloads. With more than 10,000 organizations worldwide — including over half of the Fortune 500 — relying on Databricks, and a team of 7,000+ employees, we are at the forefront of the data and AI revolution. We have been recognized as a leader by Gartner, Forrester, and IDC, and have raised more than $4 billion in funding at a $62 billion valuation.

The Impact You Will Have

• Executive translation. Translate complex data science findings into clear, actionable narratives for the CEO, C-suite, and Board of Directors — ensuring data science insights directly inform the company's most critical decisions.
• Statistical authority. Serve as the company's chief statistical voice and the final quality backstop for analytical rigor in high-stakes executive decisions. Advance the state-of-the-art in how Databricks applies statistical methods to business problems.
• Org-wide uplevel. Raise the communication bar across the entire Data Science organization by setting standards, coaching teams, and co-authoring key executive-facing deliverables. Make every DS team better at telling their story.
• Strategic insights. Produce deep strategic analyses on revenue, platform health, operational efficiency, and competitive positioning — the kind of synthesized, judgment-rich insight that AI cannot autonomously create.
• Cross-functional influence. Partner with engineering VPs, product leaders, and executive staff to embed a data-driven decision-making culture across the company. Be the trusted analytical advisor in rooms where critical decisions are made.
• External thought leadership. Represent Databricks externally as a data science thought leader at industry conferences, in publications, and in the broader statistical community. Build an external identity that attracts world-class talent.
• Methodology and standards. Define and evolve company-wide scientific methodologies — experimentation frameworks, forecasting systems, causal inference approaches — to match and push industry state-of-the-art.

What We Look For

Required

• 15+ years of experience in data science, statistics, or quantitative research spanning industry and/or academia.
• Proven track record of presenting statistical and data science concepts to C-suite and Board-level audiences, with measurable impact on executive decision-making.
• Broad expertise across data science disciplines: experimentation, causal inference, forecasting, optimization, and machine learning.
• Exceptional written and verbal communication — the ability to make complex statistical concepts intuitive and compelling for non-technical executives.
• Track record of upleveling teams: setting analytical standards, mentoring senior data scientists, and improving org-wide output quality.
• Experience at the intersection of statistics and large-scale technology or data platforms.
• Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.

Preferred

• Academic research or teaching background in statistics or a quantitative field.
• Industry experience at multiple tier-1 technology companies.
• Published research or recognized thought leadership in applied statistics.
• Experience building or leading a "Chief Statistician" or equivalent function.
• Experience in infrastructure, platform, or systems-oriented data science.