Senior Data Scientist II

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Quick Summary

Key Responsibilities

Advanced Analytics & Modeling Design, build, and deploy predictive and causal models that power personalization, retention, and monetization strategies. Apply advanced statistical methods,

Requirements Summary

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,

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Data ScientistData

About the Role:

Fetch is at a major inflection point in leveraging data to drive business growth and innovation. With over $100B in item-level purchase data from millions of monthly active users, we are uniquely positioned to turn raw consumer insights into actionable intelligence that powers every aspect of our product, operations, and monetization strategies.

We are seeking a Senior Data Scientist to play a key role in developing and scaling Fetch’s data science capabilities. This role transcends traditional analytics as you will architect and operationalize production-ready models and frameworks that directly influence Fetch’s product strategy, personalization systems, and business outcomes. As a Senior Data Scientist, you will partner cross-functionally with Product, Engineering, Marketing, and Data Product teams to transform complex datasets into measurable business impact through experimentation, predictive modeling, and data-driven decision-making.

Within your first year, you will lead multiple high-impact initiatives such as designing predictive models for engagement and churn, optimizing personalization systems through experimentation and machine learning, and developing scalable frameworks that quantify the business impact of new product launches and feature iterations.

What you’ll do at Fetch:

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.

Minimum Requirements:

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.

Preferred Requirements:

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.

This is a full-time role that can be held from one of our US offices or remotely in the United States.