Note: The job is a remote job and is open to candidates in USA. Fetch is at a major inflection point in leveraging data to drive business growth and innovation. They are seeking a Senior Data Scientist II to develop and scale their data science capabilities, influencing product strategy and business outcomes through advanced analytics and collaboration across teams.
Responsibilities
- Design, build, and deploy predictive and causal models that power personalization, retention, and monetization strategies
- Apply advanced statistical methods, including Bayesian inference, causal impact analysis, and hierarchical modeling, to guide decision-making
- Develop and operationalize experimentation and measurement frameworks that ensure accurate attribution and reproducibility across Fetch’s products
- Quantify the impact of key business and product initiatives, translating complex model outputs into actionable insights
- Design and analyze experiments that test hypotheses about user behavior, product features, and marketing initiatives
- Establish metrics and analytical frameworks that measure Fetch’s progress toward strategic growth and retention goals
- Partner closely with Product, Engineering, and Data Product teams to transform insights into scalable data products and intelligent systems
- Communicate complex analyses through clear narratives and visualizations that drive executive understanding and action
- Mentor and collaborate with peers to strengthen Fetch’s scientific rigor, data culture, and analytical storytelling capabilities
- Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to build and scale robust data science solutions
- Champion best practices in experimentation, model validation, reproducibility, and governance
- Advance Fetch’s use of AI/ML tools for automation, documentation, and anomaly detection, emphasizing validation and responsible use
Skills
- 8+ years of experience in data science, machine learning, or applied analytics with proven impact in product-driven environments
- Deep expertise in statistical modeling, experimental design, and causal inference
- Strong proficiency in SQL and at least one programming language (Python preferred)
- Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
- Proven ability to communicate complex technical insights to non-technical stakeholders and drive strategic decision-making
- Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field
- Advanced degree (Master's or Ph.D.) in a quantitative discipline
- Experience deploying ML models into production and managing model lifecycle and performance
- Background in consumer technology, ad tech, or personalization systems
- Experience building frameworks that improve experimentation velocity and decision quality
- Familiarity with privacy-preserving data modeling and compliance standards such as GDPR or CCPA
- Mentorship experience or demonstrated leadership in scientific or analytical development
Benefits
- Competitive compensation packages including base, equity, and benefits
Company Overview