Drive end-to-end data initiatives from problem framing and experimental design to delivery, including proof-of-concepts, stakeholder validation, and handoff to production-style patterns (orchestrated pipelines, dbt models, and production-grade data products).
Refine the datasets and logic supporting strategic motions, such as funnel engagement behavior, cross-sell/risk signals, and adoption analytics for high-visibility sales programs.
Collaborate across Data & AI and the business (Product, GTM, Marketing and Sales) to resolve ambiguity and align on trade-offs regarding scope, quality, and compliance.
Apply LLM-assisted methods to accelerate synthesis and code development while owning the validation, reproducibility, and human-in-the-loop review for all outputs affecting business, customer and partner stakeholders.
Translate advanced technical work and novel methodologies into clear, jargon-free recommendations for senior leadership to facilitate data-driven decision-making.
Mentor analysts and data scientists on analysis design, statistical rigor, and stakeholder management; guide the team through enterprise platform norms such as masking and data-product operationalization.

5–8+ years of professional experience manipulating large datasets, building analytical pipelines, and deploying statistical or predictive models.
Strong mastery of Python (specifically Pandas and enterprise cloud libraries) and expert-level SQL (Snowflake/DBeaver environments).
Comfort treating AI as a primary development collaborator, using prompt engineering and modern IDEs to increase coding velocity and automate manual tasks.
Solid experience with GitHub workflows and a process-engineering mindset—you enjoy building automated data validation scripts to proactively catch and prevent recurring data issues.
Solid practical knowledge of regression, simulation, scenario analysis, clustering, and decision trees applied to real-world business problems.
Ability to build clear, scannable data narratives across various mediums (slide decks, dashboards, and reporting frameworks) using at least one major enterprise BI platform.
Experience operating within tech/SaaS business models—ideally supporting Sales Operations, Finance, GTM strategy, or lifecycle analytics is highly preferred.
Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related quantitative field.

Comprehensive medical, dental, and vision coverage
Flexible Spending Account
healthcare and dependent care
Health Savings Account
high deductible medical plan
Retirement 401(k) with employer match
Paid time off and holidays
Paid parental leave plans for all new parents
Leave benefits including disability, paid family medical leave, and paid military leave
Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Senior Data Scientist – Applied Analytics, Data & AI

Key skills