Staff Data Scientist, ML (People Analytics & Insights)

About the role

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

Responsibilities

• Spearhead the next phase of talent intelligence: Take the team beyond descriptive reporting and build the predictive frameworks that show not just what is happening in our workforce, but what will happen next.
• Architect a unified workforce data model: Pipeline data across disparate recruiting systems, performance cycles, surveys, and internal tools into a single, cohesive data model that maps the entire employee lifecycle; use AI-native workflows aggressively to parse unstructured text like exit notes and survey feedback at scale.
• Define the metrics dictionary and semantic layer: Standardize how metrics like headcount, attrition, and workforce trends are measured across the company; build the semantic layers that keep this data consistent and trustworthy at scale.
• Drive data access control and governance: Build the frameworks for role-based access controls and data masking so HR, Finance, and line managers have exactly the access they need without risking sensitive personnel data.
• Redesign employee sentiment architecture: Replace traditional annual survey cycles with a continuous, always-on listening framework that captures real-time organizational health and highlights leading risk indicators.
• Own product delivery: Act as the technical product owner for internal data interfaces—collaborating directly with Enterprise Engineering to ensure exceptional user utility, predictive accuracy, and data reliability.
• Enforce rigorous statistical standards: Apply experimental design, A/B testing, and psychometric methodologies to ensure our predictive workforce models and survey frameworks are scientifically backed and statistically valid.

Requirements

7+ years of data science experience, with advanced skills in Python, SQL, and direct experience with modern data infrastructure like Snowflake, BigQuery, or dbt. Strong product focus and experience defining user requirements, collaborating with engineers, and taking internal data tools from conception to launch. Deep understanding of statistics, experimental design, and psychometrics or survey methodology to design research-backed questions. Direct experience integrating language models into data pipelines to automate text processing and summarization at scale.

Qualifications

Must have a strong background in data science, machine learning, and statistics. Experience with large-scale data processing and analysis, including experience with Snowflake, BigQuery, or dbt. Proven ability to design and implement predictive models and analyze complex datasets. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.

Skills

• Advanced skills in Python, SQL, and modern data infrastructure like Snowflake, BigQuery, or dbt.
• Experience with large-scale data processing and analysis.
• Proven ability to design and implement predictive models and analyze complex datasets.
• Excellent communication and collaboration skills.

Benefits

Challenging, high-impact work to grow your career. Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching. Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents. Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more. Employer-paid life & disability insurance, fertility benefits, and mental health benefits. Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!

Pay

$217k - $255k

Schedule

Hybrid