Staff Data Scientist

The Predictive Index•Westwood, MA

1d•$170,000 - $220,000•Hybrid

About The Position

The Predictive Index is seeking a Staff Data Scientist to establish and lead the data science function for a new venture. This role involves defining the discipline, setting methods, standards, and infrastructure, and owning the evidence behind all claims, metrics, and insights. The ideal candidate will have experience building rigorous data science practices from the ground up and will operate with significant autonomy within a venture that combines startup independence with the credibility of an established science brand. This is an opportunity to set the scientific direction and build a foundational function that drives product value and strategy.

Requirements

7+ years of substantial, staff-level experience as a data scientist in product environments.
Experience developing strong, defensible opinions on data science methodologies.
Track record of building product analytics from scratch and owning them end to end.
Comfortable in code, having personally stood up instrumentation, pipelines, and dashboards in live product environments.
Deep expertise running product experiments with statistical rigor.
Ability to determine when a result is real, noise, or unanswerable by the design.
Ability to defend methodology and teach it to non-quantitative audiences.
Ability to operate as the sole subject matter expert, setting direction independently.
Fluency in translating ambiguous business questions into tractable data problems.
Fluency in translating data answers into actionable decisions for Product, GTM, and leadership.
Comfort working at the frontier where research, product, and GTM strategies are still being defined.
Maturity to bring order to ambiguity.
Graduate degree (or equivalent applied experience) in Statistics, Data Science, Computer Science, Econometrics, Quantitative Psychology, or a closely related quantitative field.
Passion for using AI in all aspects of work.
A builder's mindset and seniority.
Willingness to cover surface area well beyond the title and own outcomes.

Nice To Haves

Experience building a data science function before.

Responsibilities

Own the evidence layer of the venture, end to end, turning product and customer signal into defensible knowledge.
Build a repeatable function for generating insights about client outcomes.
Set the standard for rigor by defining experimental methods, statistical bars, and analytical practices.
Act as the final authority on the validity and generalizability of results.
Build the instrumentation, data pipelines, dashboards, and analytics infrastructure from scratch.
Make architectural decisions for future data science infrastructure.
Identify key drivers of client outcomes by correlating product signals.
Separate genuine drivers of success from superficial ones.
Design and run cohort and funnel experiments to validate hypotheses.
Build feedback loops to compound the venture's advantage.
Partner with Product, GTM, and Behavioral Science as a peer decision-maker.
Shape the roadmap, market thesis, and strategic bets through evidence.
Establish practices, documentation, and standards for scaling the data science function.