Senior Data Scientist II

Responsibilities

Advanced Analytics & Modeling

• Design, build, and deploy predictive and causal models supporting personalization, retention, and monetization.
• Apply Bayesian inference, causal impact analysis, and hierarchical modeling to guide decisions.
• Develop and operationalize experimentation and measurement frameworks with accurate attribution and reproducibility.

Business Impact & Experimentation

• Quantify the impact of business and product initiatives and translate model outputs into actionable insights.
• Design and analyze experiments involving user behavior, product features, and marketing initiatives.
• Establish metrics and analytical frameworks for growth and retention goals.

Collaboration & Influence

• Partner with Product, Engineering, and Data Product teams to turn insights into scalable data products and intelligent systems.
• Communicate complex analyses through clear narratives and visualizations for executive decision-making.
• Mentor peers and strengthen scientific rigor, data culture, and analytical storytelling.

Technical Excellence

• Use Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to build scalable data science solutions.
• Champion experimentation, model validation, reproducibility, and governance best practices.
• Advance AI/ML tools for automation, documentation, and anomaly detection with appropriate validation and responsible use.

Requirements

• 8+ years of experience in data science, machine learning, or applied analytics in product-driven environments.
• Deep expertise in statistical modeling, experimental design, and causal inference.
• Strong SQL proficiency and proficiency in at least one programming language, preferably Python.
• Experience with large-scale data systems such as Snowflake, dbt, Airflow, or Spark.
• Ability to communicate technical insights to non-technical stakeholders and drive strategic decisions.
• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

Nice-to-Haves

• Master’s or Ph.D. in a quantitative discipline.
• Experience deploying machine learning models to production and managing model lifecycle and performance.
• Consumer technology, advertising technology, or personalization systems experience.
• Experience building frameworks that improve experimentation velocity and decision quality.
• Familiarity with privacy-preserving data modeling and GDPR or CCPA compliance.
• Mentorship experience or leadership in scientific or analytical development.

Compensation & Benefits

• Equity for full-time employees.
• Dollar-for-dollar 401(k) match up to 4%.
• Medical, dental, and vision plans, including pet coverage.
• Up to $10,000 per year in education reimbursement.
• Employee Resource Groups.
• Flexible paid time off, nine paid holidays, and a year-end week-long break.
• Paid parental leave and flexible return-to-work arrangements.
• One-time $2,000 Calvin Care Cash incentive for eligible employees welcoming new family members.
• Flexible remote work environment with provided hardware and software.