Senior Data Scientist

Role overview

• check_circle Develop, implement, and maintain predictive and propensity models to forecast customer behavior, including purchase likelihood, churn risk, and campaign responsiveness.
• check_circle Apply statistical and machine learning techniques to large-scale datasets to drive measurable business outcomes.
• check_circle Design, validate, and monitor models to ensure ongoing performance, reliability, and business relevance.
• check_circle Translate model outputs into actionable business strategies that improve conversion, retention, and lifetime value.
• check_circle Partner with marketing and product teams to optimize campaign performance through data-driven insights.
• check_circle Design and execute A/B tests and other controlled experiments to measure incremental impact and improve marketing effectiveness.
• check_circle Identify opportunities to improve targeting, segmentation, and personalization strategies.
• check_circle Balance speed, cost, and analytical rigor to support timely business decisions.
• check_circle Ensure data integrity, quality, and compliance with applicable privacy regulations (including GDPR and CCPA).
• check_circle Build dashboards, reports, and visualizations that clearly communicate findings to technical and non-technical stakeholders.
• check_circle Challenge assumptions, surface risks, and provide independent analytical perspective to senior leadership.
• check_circle Maintain strong documentation and governance practices across models and analyses.
• check_circle Not a purely reporting or dashboard-production role.
• check_circle Not a junior or supervised modeling position.
• check_circle Not a data engineering or infrastructure-only role.
• check_circle Not a theoretical research position detached from business impact.
• check_circle Not a marketing execution role without analytical ownership.
• check_circle 5+ years of experience in data science, marketing analytics, or a related quantitative role, preferably in a B2C subscription or performance-driven environment.
• check_circle Proven experience building and deploying predictive models, including logistic regression, tree-based models, and gradient boosting techniques.
• check_circle Strong proficiency in Python or R for data analysis and modeling.
• check_circle Advanced SQL skills for querying and manipulating large datasets.
• check_circle Experience designing and interpreting experiments, including A/B testing and causal analysis.
• check_circle Strong understanding of statistical methods, machine learning algorithms, and model validation techniques.
• check_circle Experience translating analytical findings into strategic recommendations for business stakeholders.
• check_circle Ability to operate independently in a fast-paced, cross-functional environment.
• check_circle Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.

Preferred qualifications

• Experience working with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with customer segmentation, lifetime value modeling, or attribution modeling.
• Familiarity with marketing analytics platforms and CRM systems.
• Advanced degree in a quantitative discipline.

Benefits

• check_circle 100% company-paid Medical, Dental, and Vision coverage
• check_circle Generous bonus package
• check_circle Unlimited Vacation policy
• check_circle Paid Sick Leave and Paid Holidays
• check_circle 401(k) Plan with company match
• check_circle Daily company-paid lunches for onsite employees
• check_circle Paid Parental Leave and Dependent Care support
• check_circle Student Loan Repayment Program and 529 Education Savings Plan
• check_circle Training and Education Reimbursement
• check_circle Paid Parking
• check_circle Pet Insurance and Employee Referral Rewards
• check_circle Dog-friendly office, complimentary snacks, beverages, and on-site gym

About the company