Staff Data Scientist: Hybrid Product & Growth Analytics

TaskRabbit, Inc.; San Francisco (CA); Hybrid; USD 170,000 - 225,000; Full time

Benefits offered by this job

Health insurance

401k match

2 company-wide closure weeks

Product stipends

Wellness stipend

IKEA discounts

Generous time off

Job summary

TaskRabbit is seeking a Staff Data Scientist to join our data science team in San Francisco. You’ll partner with product and commercial operations to define high-impact analytical problems, run experiments, and deliver insights that influence product growth and reduce marketplace losses.

Ideal candidates have 7+ years in data science, strong SQL, Python, dbt and ML Ops familiarity, and a proven ability to communicate complex findings to executives. This hybrid role requires in-office Tue/Wed.

Qualifications

• BS, MS or Ph.D. in a quantitative field.
• Minimum of 7 years industry experience in data science.
• Strong experience with advanced experimentation and statistical modeling.
• Excellent analytical and problem-solving skills.
• Excellent business acumen and strategic thinking in commerce/risk domains.
• Proficient in SQL and Python; familiar with data pipelines (dbt) and Git; bonus for ML productionizing and ML Ops.
• Self-starter with independent project ownership and demonstrated business impact.
• Able to communicate complex data findings to executives.

Responsibilities

• Define high-impact analytical problems with stakeholders and present actionable insights.
• Perform analytical deep dives to identify growth opportunities in product areas.
• Collaborate to define success metrics for features, run experiments, and optimize experiences.
• Lead Data Science initiatives (experimentation systems, data agents, eventing) and promote data-driven culture.

Skills

SQL

Python

dbt

Git

ML Ops

Productionizing ML

Education

BS/MS/PhD in quantitative field

Job description

TaskRabbit is seeking a Staff Data Scientist to join our data science team in San Francisco. You’ll partner with product and commercial operations to define high-impact analytical problems, run experiments, and deliver insights that influence product growth and reduce marketplace losses.

Ideal candidates have 7+ years in data science, strong SQL, Python, dbt and ML Ops familiarity, and a proven ability to communicate complex findings to executives. This hybrid role requires in-office Tue/Wed.