Data Scientist

About This Role

Join as a Staff Data Scientist to partner with Partnerships and Finance departments, developing strategic models, metrics, and experiments to optimize partner relationships and drive growth. Shape partner onboarding, measurement, and pricing strategies using data-driven insights.

Responsibilities

• Act as a strategic data thought partner to Partnerships and Finance teams, providing analysis and recommendations.
• Lead the development and standardization of partner performance measurement by defining KPIs and creating scorecards.
• Embed data collection and measurement requirements across the entire partner lifecycle, from contract negotiations to onboarding.
• Drive analytics related to partner onboarding, aligning tracking schemas with Data Engineering, Product, and Engineering teams.
• Own pricing strategy analytics, including elasticity measurement, pricing tests, and tradeoff analysis.
• Design and analyze experiments, including A/B and multivariate tests, and conduct causal inference studies.
• Develop and refine attribution models for partners and channels to inform spend allocation and strategic planning.
• Proactively identify new opportunities through in-depth analyses, root cause investigations, and opportunity sizing.
• Collaborate with Data Engineering to develop durable, production-grade analytics pipelines.
• Communicate complex insights clearly and effectively to stakeholders, supporting ad hoc analyses and strategic decision-making.

Requirements

• 7+ years of experience in data science, decision science, or advanced analytics
• Advanced proficiency in SQL
• Strong skills in Python for analysis, modeling, and reproducible workflows
• Experience working with modern data stacks (Snowflake, Airflow, GA4/Segment, GitHub, ThoughtSpot/Tableau, Hex/Jupyter)
• Exceptional data storytelling skills
• Business acumen in pricing, partner economics, and financial modeling
• Experience partnering with engineers on instrumentation, data quality, and system integrations
• Expertise in metric development, experimentation (test design, power analysis, evaluation methodologies)
• Hands-on experience with causal inference techniques (diff-in-diff, matching, synthetic control methods)
• Knowledge of AI/ML techniques (uplift modeling, classification, propensity scoring, forecasting)
• Strong analytical mindset

Qualifications

• 7+ years of experience in data science, decision science, or advanced analytics with a proven track record of influencing senior stakeholders and delivering measurable business outcomes.

Skills

* Required skills

Benefits