Back to jobs

Data Scientist - Music Mission

New York, NY

Pay
USD 116,994–167,135/yearAnnual period assumed · Plus equity — pay source
This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $116,994 - $167,135 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
Read the full posting
Work setup
Unconfirmed
Employment
Permanent — employment source
Employment type Permanent
Read the full posting
Apply at Spotify

What you’ll work on

Full posting
  • In this role, you'll partner closely with product managers and ML engineers to evaluate and improve the models that power Discovery Mode.

  • Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization

  • Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact

From the employer’s posting
We're looking for a Data Scientist to join Discovery Mode within the Music Mission. Discovery Mode is a tool for artists and music marketers designed to help find new listeners when it matters most. With Discovery Mode, artists and labels identify songs that are a priority, and our systems use that signal to inform the algorithms that power personalized recommendations. This role sits within the ML squad that builds and operates the models behind Discovery Mode's measurement system, and you'll serve as the squad's analytical lead. In this role, you'll partner closely with product managers and ML engineers to evaluate and improve the models that power Discovery Mode. You'll tackle complex analytical problems by designing experiments, developing evaluation frameworks, and building the analytical foundations that help keep our models accurate, reliable, and impactful for artists. As part of the Product Insights team within Music Mission, you'll help shape the measurement systems behind one of Spotify's most important promotion products. What You'll Do
What You'll Do Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact
Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact Design and execute rigorous experiments to evaluate model quality, measure outcomes, and guide model development

What you’ll bring

All qualifications

Core experience

  • You have 4+ years of experience in a data science role and a degree in data science, statistics, economics, mathematics, or a related quantitative field
  • You have experience measuring customer outcomes, defining KPIs, and connecting analytical insights to product decisions
  • You have experience evaluating machine learning model performance and partnering with ML engineers to improve model and customer outcomes
  • You have experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale
Qualification wording
You have 4+ years of experience in a data science role and a degree in data science, statistics, economics, mathematics, or a related quantitative field
You have experience measuring customer outcomes, defining KPIs, and connecting analytical insights to product decisions
You have experience evaluating machine learning model performance and partnering with ML engineers to improve model and customer outcomes
You have experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale

Tools in this posting

  • Python
  • SQL
  • BigQuery
  • dbt
Source — Tool mentions in context
- You communicate complex statistical concepts clearly to both technical and non-technical audiences - You have strong data science fundamentals, including Python, SQL, BigQuery, dbt, data storytelling, and experience working within cross-functional product teams - You have experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale

Job description

View original posting ↗

The Music Mission enables music creators to grow, engage, and monetize their fan bases on Spotify. Central to the Music Mission's vision is the development of promotional tools for artists and label teams, powered by Spotify's deep knowledge of listener behavior. Products like Discovery Mode, Marquee, Showcase, Music Videos, and Clips help artists and their teams grow their audiences, connect with fans, and achieve their goals on Spotify.

We're looking for a Data Scientist to join Discovery Mode within the Music Mission. Discovery Mode is a tool for artists and music marketers designed to help find new listeners when it matters most. With Discovery Mode, artists and labels identify songs that are a priority, and our systems use that signal to inform the algorithms that power personalized recommendations. This role sits within the ML squad that builds and operates the models behind Discovery Mode's measurement system, and you'll serve as the squad's analytical lead.

In this role, you'll partner closely with product managers and ML engineers to evaluate and improve the models that power Discovery Mode. You'll tackle complex analytical problems by designing experiments, developing evaluation frameworks, and building the analytical foundations that help keep our models accurate, reliable, and impactful for artists. As part of the Product Insights team within Music Mission, you'll help shape the measurement systems behind one of Spotify's most important promotion products.

What You'll Do

  • Own the analytical function for the Discovery Mode ML squad, driving evaluation and continuous improvement of the models that power measurement and campaign optimization
  • Partner with ML engineers to develop evaluation frameworks and identify opportunities to improve model performance, reliability, and customer impact
  • Design and execute rigorous experiments to evaluate model quality, measure outcomes, and guide model development
  • Conduct deep-dive analyses to assess model performance and translate findings into clear, actionable recommendations for product and business stakeholders
  • Build, maintain, and evolve dashboards that track model health, customer metrics, and program performance
  • Collaborate with product managers, engineers, and cross-functional partners to align analytical priorities with squad goals and customer needs
  • Contribute to the broader Product Insights community by sharing best practices and helping raise the bar for analytics across Discovery Mode

Who You Are

  • You have 4+ years of experience in a data science role and a degree in data science, statistics, economics, mathematics, or a related quantitative field
  • You have experience measuring customer outcomes, defining KPIs, and connecting analytical insights to product decisions
  • You know how to design and implement A/B tests, understand when experimentation is the right tool, and interpret results with appropriate rigor
  • You have experience evaluating machine learning model performance and partnering with ML engineers to improve model and customer outcomes
  • You are comfortable working in a highly technical environment and collaborating closely with engineering partners
  • You communicate complex statistical concepts clearly to both technical and non-technical audiences
  • You have strong data science fundamentals, including Python, SQL, BigQuery, dbt, data storytelling, and experience working within cross-functional product teams
  • You have experience in areas such as advertising measurement, recommendation systems, experimentation, or causal inference at scale

Where You'll Be

  • We offer you the flexibility to work where you work best! For this role, you can be within the EST timezone region as long as we have a work location.
  • This team operates within the Eastern Standard time zone for collaboration.
The United States base range for this position is $116,994 - $167,135 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
 
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
 

Employment type

Permanent

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on jobs.lever.co. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $116,994 - $167,135 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future. Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
Location & working pattern

New York, NY

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Jun 23, 2026
Recorded sightings
65
Last seen by us
Oct 8, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.