Home › Companies › Spotify › Data Scientist - Discovery Mode
Data Scientist - Discovery Mode
Spotify · New York, NY · Remote · Active · Lever
Job facts
| Field | Value |
|---|---|
| Company | Spotify |
| Title | Data Scientist - Discovery Mode |
| Normalized title | - |
| Department / team | Data and Analytics / Music |
| Location | New York, NY, United States |
| Work model | Remote / Remote |
| Employment type | Permanent |
| Salary | - |
| Status | active |
| ATS provider | Lever |
| Posted / first seen | 2026-06-22 / 2026-06-23 |
| Changed / last seen | 2026-06-23 / 2026-06-23 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Spotify. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Lever. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in New York. | Open |
| Department jobs | Active postings in Data and Analytics. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Spotify |
| Source | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| ATS provider | Lever |
Description
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.
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.
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.
Full job record
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| Org ID | 72fe3b06-0d08-4f7d-9dfd-beedeeda0a25 |
| Source ID | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| Board ID | 8f76458c-d40f-4324-bb14-bb757d1b7058 |
| Provider | lever |
| Provider Job Key | 1bbaf909-5ff3-4ed6-87ca-f7ff007a169c |
| Title | Data Scientist - Discovery Mode |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | New York, NY |
| Department | Data and Analytics |
| Team | Music |
| Employment Type | Permanent |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | NY |
| City | New York |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.lever.co/spotify/1bbaf909-5ff3-4ed6-87ca-f7ff007a169c |
| Apply URL | https://jobs.lever.co/spotify/1bbaf909-5ff3-4ed6-87ca-f7ff007a169c/apply |
| First Seen At | 2026-06-23 07:56:53Z |
| Last Seen At | 2026-06-23 07:56:53Z |
| Last Checked At | 2026-06-23 07:56:53Z |
| Last Changed At | 2026-06-23 07:56:53Z |
| Inactive At | — |
| Source Posted At | 2026-06-22 17:14:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=lever/board=spotify/date=2026-06-23/2026-06-23T07-56-53-337Z-25fb3c1fb125f8989660dc7f15cd809588d3999d4185827e0e1ccff4ee2d857f.json |
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