Senior Data Scientist

Remote (United States)

Job Details

Location: United States

Workplace: Remote

Employment Type: Full-time

Experience: 7+ years in Data Science

Core Areas: Statistical Modeling, Machine Learning, Experimental Design, Bayesian Analysis, Natural Language Processing (NLP), Large Language Models (LLMs), Python, Advanced SQL

Compensation: $190,500 annually, plus equity

Schedule: Flexible hours with no core working hours; approximately 40 hours per week

Travel: At least two team gatherings annually, typically lasting 4–5 days each

About the Role

This opportunity is for a Senior Data Scientist to lead complex, high-impact data science initiatives involving statistical modeling, machine learning, experiment design, Bayesian marketing analysis, and production classifier implementation. The position focuses on translating complex and privacy-constrained datasets into actionable product and business insights, improving search and AI-powered experiences, evaluating marketing performance, and optimizing revenue-related decisions.

The role combines advanced quantitative analysis with hands-on development using Python, SQL, machine learning, natural language processing, and large language models. Responsibilities span the full data science lifecycle, from defining analytical problems and designing experiments to implementing production solutions, monitoring performance, and communicating findings to product stakeholders. Success requires independent project ownership, strong statistical reasoning, and the ability to generate reliable insights from sparse data while maintaining rigorous privacy standards.

What You'll Do

• Lead complex data science projects from initial scoping and experimental design through implementation, production deployment, performance evaluation, and post-project analysis.
• Develop and apply statistical models to investigate product behavior, quantify business performance, and support evidence-based decisions.
• Design, implement, and analyze experiments across digital product experiences, including search functionality, AI-assisted answers, and revenue optimization initiatives.
• Apply Bayesian statistical methods to marketing campaign analysis, measuring campaign effectiveness and translating full-funnel performance data into actionable recommendations.
• Define core product growth metrics and develop analytical infrastructure to monitor trends, performance changes, and anomalies.
• Build and improve monitoring pipelines that identify unexpected shifts in search traffic patterns with greater speed and reliability.
• Develop, deploy, evaluate, and refine machine learning models and classifiers in production environments.
• Apply natural language processing techniques and large language models to improve AI-powered product functionality and analytical capabilities.
• Contribute to AI model evaluation and implementation, including approaches involving LLM fine-tuning, LLM-as-judge methodologies, and AI-assisted development.
• Expand evaluation datasets used for page context understanding, including complex scenarios involving multi-tab browsing and content reattachment.
• Improve classifier and trigger systems that determine when AI-assisted answers appear in search results, balancing output quality with privacy requirements.
• Analyze sparse, privacy-constrained datasets to identify meaningful patterns, assess statistical confidence, and develop defensible recommendations.
• Use advanced SQL and analytical databases to extract, transform, query, and investigate complex datasets.
• Collaborate with product teams to translate analytical findings into product improvements, measurable growth opportunities, and informed business decisions.
• Take ownership of technical and analytical deliverables while contributing to the effectiveness and throughput of cross-functional teams.

Qualifications

Required Experience

• At least 7 years of professional experience in Data Science.
• Demonstrated success leading highly complex data science projects from problem definition and scoping through production implementation with minimal supervision.
• Experience designing, implementing, and analyzing experiments across product experiences.
• Experience deriving actionable insights from sparse datasets or data subject to privacy constraints.

Required Skills

• Strong expertise in statistical modeling, quantitative analysis, experimental design, and evidence-based decision-making.
• Ability to write production-grade Python code or use a comparable high-level programming language.
• Advanced SQL proficiency, including query optimization and efficient analysis of complex datasets.
• Familiarity with columnar analytical databases such as BigQuery, ClickHouse, Redshift, or Druid.
• Ability to design and evaluate experiments, interpret results, and translate findings into actionable product recommendations.
• Strong analytical problem-solving skills, particularly when working with incomplete, sparse, or privacy-constrained data.
• Ability to collaborate effectively with product teams and contribute to overall team productivity.
• Ability to independently manage complex technical projects and deliver production-ready analytical solutions.
• Practical capability in at least two of the following four areas:
  • Deploying and iterating on machine learning models in production environments.
  • Developing and deploying natural language processing (NLP) solutions.
  • Applying large language model technologies, including fine-tuning, LLM-as-judge, and AI-assisted development.
  • Conducting marketing campaign analysis using Bayesian statistical methods.

Preferred Qualifications

• Experience with business intelligence and data visualization platforms such as Tableau or Power BI.

Benefits

• Flexible working hours without a fixed core-hours requirement.
• Company-sponsored health benefits for eligible U.S.-based team members.
• Paid parental leave.
• Home office setup support and coworking allowances.
• Participation in at least two annual team gatherings, including an all-hands meetup and a team retreat, each typically lasting 4–5 days. Attendance is strongly encouraged, with consideration for extenuating circumstances.
• Participation in video conferences with cameras enabled is required.
• Successful completion of a background check is required as a condition of employment.