Similar Jobs
Fintech • Machine Learning • Payments • Software • Financial Services
The role involves developing and deploying personalized recommendation engines using advanced ML techniques, while collaborating with cross-functional teams to drive impactful customer experiences.
Top Skills:
AWSCondaH2OPythonSpark
Fintech • Machine Learning • Payments • Software • Financial Services
The role involves leading a team to develop machine learning models for personalized customer experiences, leveraging large datasets and advanced techniques, while collaborating with cross-functional teams.
Top Skills:
AWSCondaDaskH2OPysparkPythonPyTorchSpark
Blockchain • Cloud • Fintech • Information Technology • Software • Cryptocurrency • Web3
As a Data Analytics Engineer, you'll design clean datasets in Snowflake for AI tooling, ensuring teams access reliable data for decision-making.
Top Skills:
DbtSnowflakeSQL
Join our Personalization Surfaces Data Science team and help shape how we evaluate and improve Spotify’s user experience. In this role, you’ll build scalable tools and insights that integrate qualitative and quantitative signals—such as user behavior, sentiment, and customer care insights—to holistically assess product quality.
This is a Data Scientist II individual contributor role for someone passionate about the intersection of behavioral data, user research, and product development. You’ll collaborate closely with user researchers, engineers, PMs, and fellow data scientists to diagnose friction, inform iteration, and ensure we’re building experiences users truly value.
What You'll Do
- Build tools and pipelines that combine user behavior data, in-app feedback, surveys, and qualitative research to evaluate product experiences across Spotify surfaces.
- Develop frameworks to assess product quality and user sentiment at scale, enabling teams to monitor product health over time.
- Collaborate with user researchers to design, interpret, and integrate studies into data-driven product strategies.
- Communicate findings clearly and persuasively to stakeholders across product, engineering, and design.
Who You Are
- You have experience as a data scientist or analytics professional working on consumer-facing products.
- You are proficient in SQL and Python and skilled at developing analytics workflows using tools like BigQuery and dbt.
- You think analytically and can structure ambiguous problems using mixed-methods evidence, including knowledge of survey design and statistics.
- You’ve worked with both behavioral data (e.g. impressions, clicks) and qualitative inputs (e.g. survey free-text) to drive actionable insights.
- You’re an excellent communicator who synthesizes insights across disciplines to guide product development.
- You demonstrate a growth mindset, seek feedback, and support the development of those around you.
- You embody Spotify’s values: Passionate, Innovative, Sincere, Collaborative, and Playful.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North Americas 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 $ 143,023 - $ 204,319, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, a monthly meal allowance, 23 paid days off, 13 paid flexible holidays. 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.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Spotify New York, New York, USA Office
4 World Trade Center, New York, NY, United States, 10007
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory


