Discovery Mode Data Scientist - Growth & Measurement

Spotify AB; New York (NY); Hybrid; USD 117,000 - 167,000; Full time

Benefits offered by this job

Health insurance

Six‑month parental leave

401(k) retirement plan

Meal allowance

Paid time off

Flexible holidays

Paid sick leave

Equity

Job summary

Spotify AB in New York is seeking a Data Scientist to lead analytical efforts for Discovery Mode within the Music Mission. You will design experiments, build evaluation frameworks, and partner with ML engineers to improve models and measure impact for artists and marketers.

Join the Product Insights team to translate data into actionable recommendations, maintain dashboards, and influence product decisions with rigorous analytics and storytelling.

Qualifications

• 4+ years of data science experience with statistics background.
• Experience measuring customer outcomes and linking insights to product decisions.
• Proficient in designing and interpreting well‑controlled experiments.

Responsibilities

• Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of models.
• Design and run rigorous experiments to evaluate model quality and outcomes; translate results into recommendations.
• Build dashboards tracking model health, customer metrics, and program performance.
• Collaborate with product managers, engineers, and cross‑functional partners.
• Communicate complex analytics clearly to technical and non‑technical audiences.

Skills

Python

SQL

BigQuery

dbt

Data storytelling

A/B testing

Causal inference

Education

Bachelor's or higher in data science, statistics, economics, mathematics, or related field

Tools

BigQuery

dbt

Job description

Spotify AB in New York is seeking a Data Scientist to lead analytical efforts for Discovery Mode within the Music Mission. You will design experiments, build evaluation frameworks, and partner with ML engineers to improve models and measure impact for artists and marketers.

Join the Product Insights team to translate data into actionable recommendations, maintain dashboards, and influence product decisions with rigorous analytics and storytelling.