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Director Spotify Data Science Jobs (NOW HIRING)

As Director of Data Science, you will lead the team responsible for Numerator's consumer panel - the quality, currency, and representativeness of the signal at the heart of our data. Your team owns ...

As Director of Data Science, you will lead the team responsible for Numerator's consumer panel - the quality, currency, and representativeness of the signal at the heart of our data. Your team owns ...

As part of the Business Intelligence team, the Director of Data Science will lead advanced analytics initiatives that translate complex data into actionable recommendations across ticketing, retail ...

Your Opportunity We are hiring a Director, Data Science to own and lead all Ads Data Science for Chewy--fully accountable for the science strategy and production implementation behind Chewy's onsite ...

Your Opportunity We are hiring a Director, Data Science to own and lead all Ads Data Science for Chewy-fully accountable for the science strategy and production implementation behind Chewy's onsite ...

The Director, Data Science will lead the team responsible for turning the data generated by our fleet, simulation environment, and ML systems into the insights, evaluations, and decisions that make ...

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Director Spotify Data Science information

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$54K

$154.9K

$244K

How much do director spotify data science jobs pay per year?

As of Sep 9, 2026, the average yearly pay for director spotify data science in the United States is $154,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $189,500.00 per year, depending on experience, location, and employer.

What does a director of data science do at Spotify?

A Director of Data Science at Spotify leads teams of data scientists and analysts to drive business strategy through data-driven insights. They oversee the development of analytical models and tools that power features like music recommendations and user personalization. This role involves collaborating with product, engineering, and business leaders to inform key decisions using data. Additionally, Directors help set the vision for data science at Spotify, ensuring the team stays innovative and impactful in a fast-changing industry.

What are the key skills and qualifications needed to thrive as a director of data science at Spotify?

To thrive as a Director of Data Science at Spotify, you need deep expertise in data analytics, machine learning, and statistics, typically supported by an advanced degree in a quantitative field and significant leadership experience. Mastery of tools such as Python, SQL, cloud platforms, and data visualization systems is essential, along with familiarity with big data ecosystems. Exceptional communication, strategic vision, and team leadership skills help drive cross-functional collaboration and innovation. These skills are crucial for developing impactful data-driven products, guiding high-performing teams, and aligning analytics initiatives with Spotify's business goals.

What are some of the primary challenges a director of data science at Spotify might face when leading cross-functional teams?

A Director of Data Science at Spotify often navigates the complexities of aligning diverse technical and business stakeholders toward shared objectives. Key challenges include translating business goals into actionable data strategies, ensuring data integrity at scale, and fostering collaboration between data scientists, engineers, and product managers. Managing and mentoring a large, multidisciplinary team requires balancing hands-on technical leadership with strategic vision. Additionally, adapting to rapidly changing music industry trends and user behaviors makes it essential to prioritize projects that deliver the most value.

What is the difference between Director Spotify Data Science vs Data Scientist Spotify?

AspectDirector Spotify Data ScienceData Scientist Spotify
Required CredentialsBachelor's/Master's/PhD in Data Science, Statistics, or related field; extensive experienceBachelor's or Master's in Data Science, Computer Science, or related field; some experience
Work EnvironmentLeadership role overseeing teams, strategic planning, cross-department collaborationHands-on data analysis, model development, reporting, and insights generation
Employer & Industry UsageCommon in tech and media companies like Spotify, focusing on data-driven decision makingEntry to mid-level role in similar environments, supporting data science initiatives

The main difference is that the Director Spotify Data Science leads teams and sets strategic goals, while the Data Scientist Spotify focuses on executing data analysis and modeling tasks. The director role requires more experience and leadership skills, whereas the data scientist role is more technical and execution-focused.

What cities are hiring for Director Spotify Data Science jobs?

Cities with the most Director Spotify Data Science job openings:

What are the most commonly searched types of Spotify Data Science jobs?

The most popular types of Spotify Data Science jobs are:

What states have the most Director Spotify Data Science jobs?

States with the most job openings for Director Spotify Data Science jobs include:

What are popular job titles related to Director Spotify Data Science jobs?

For Director Spotify Data Science jobs, the most frequently searched job titles are:

Director, Data Science

Remote

Full-time

Re-posted 29 days ago


Job description

About the role.

PURE is seeking a Director, Data Science to help professionalize, scale, and lead our data science practice as a true engineering discipline. This is a foundational role at a pivotal moment: our VP, Applied Sciences has recently joined to grow our data science capability from a handful of models to a production-grade engine influencing decisions across Claims, Underwriting, Risk Management, Distribution, and more. This Director hire will be a critical partner in making that vision real.

This is not a "manage the backlog and report upward" role. It's a builder/path-maker position for someone who is energized by establishing the patterns, frameworks, and habits that make a team consistently excellent - and who can also roll up their sleeves and be one of the principal architects of that work.

What you'll do.

  • Architect and enforce a cohesive development standard across the data science team - from exploratory analysis through experimentation, deployment, and ongoing monitoring - so that every model is built on a consistent, reusable foundation rather than in isolation.

  • Lead by example as a code-first practitioner, building modular, well-documented Python frameworks and tools that make it dramatically easier for the team to work in consistent patterns and extend prior work without reinventing it.

  • Drive experiments and model development with a "fit-for-deployment" mindset from day one - designing solutions in close partnership with Data Engineering, Analytics Engineering, MLOps, IT, and business stakeholders so that what we build can and does make it into the front-end systems where underwriters, claims handlers, risk managers, and sales staff actually do their work.

  • Serve as a principal participant in our cross-functional tech lead forum, rapidly estimating effort, shaping high-level designs, and helping build a rigorous but lightweight prioritization and roadmap process - so IDEAS always knows what it could work on, what it should work on, and exactly what is in flight.

  • Establish clear success criteria, measurement frameworks, and monitoring standards for every model - both technical (drift, accuracy, bias) and business (KPI achievement, adoption) - because a deployed model that no one is watching isn't really deployed.

  • Champion documentation-as-a-habit, not documentation-as-an-afterthought, and help embed that discipline across the team.

  • Mentor and elevate colleagues, including more junior data scientists, raising the bar on engineering standards, communication habits, and professional maturity across the team.

  • Collaborate deeply with Analytics Engineering to prototype Gold Layer data assets for new models and ensure that no model reaches production on anything less.

  • Manage competing priorities with clarity and transparency, helping ensure the team never quietly works on the wrong things and always surfaces tradeoffs early.

What you'll need.

We are looking for a technically exceptional, team-oriented leader who has done this before - not just in theory, but in practice. Someone who has personally felt the pain of a data science team where everyone builds in isolation and then went and fixed it. The ideal candidate will bring:

  • 8+ years of experience in applied, code-first data science and analytics within insurance or a closely adjacent industry (financial services, risk, or similar).

  • Demonstrated success building and enforcing reusable ML frameworks and engineering standards across a team - Python modules, shared pipelines, consistent documentation patterns, and the discipline to maintain them.

  • Hands-on expertise in the full model lifecycle: from problem framing and data exploration through feature engineering, training, validation, deployment into production systems, and continuous monitoring.

  • A collaborative instinct - someone who genuinely enjoys working across Data Engineering, Analytics Engineering, MLOps, IT, and business partners to design solutions that are feasible, integrated, and lasting, rather than self-contained.

  • Experience in or strong appetite for structured cross-functional work - tech lead forums, lightweight CBAs, roadmap estimation, and the kind of prioritization rigor that keeps a team focused on the highest-value work.

  • Strong mentorship instincts, with a track record of raising the technical bar of the people around them - not by telling them what to do, but by building frameworks that make the right way the easy way.

  • The intellectual honesty to know when a model isn't ready - to not skip steps, not paper over gaps in the data, and not declare victory before the business is actually using what was built.

  • Familiarity with P&C insurance is strongly preferred but not required for the right candidate.

About the team.

PURE Insurance is actively investing in our data, analytics, data science, machine learning (ML), and artificial intelligence (AI) capabilities. We are building a centralized Data & AI department - IDEAS (Innovation in Data Engineering, Analytics & Science) - that brings together specialists across data architecture, engineering, analytics, governance, and advanced modeling. This structure creates extraordinary opportunities for collaboration and impact across every function of the insurance ecosystem, from Claims and Underwriting to Actuarial, Product, Distribution, Finance, and more.

We work with a modern data technology stack that includes AWS, Databricks, dbt, GitHub, Hex, and Arize, while also developing in-house, production-grade software in Python when it creates a genuine competitive edge. At PURE, we embrace curiosity, craftsmanship, and a relentless pursuit of improvement. Our culture values growth, mentorship, transparency, and ownership - and we know that building something durable takes time, discipline, and a willingness to experiment, learn, and adapt.

What We Do

We're a member-owned property and casualty insurer designed exclusively for financially successful families and driven by a purpose of doing what is right for our members. We provide exceptional service, hospitality and care, we partner with our members to help prevent losses and we create smart insurance solutions at fair prices.

We aim for our members to love their insurance. It is our mission is to create a membership experience so compelling that our members never want to leave.

Who We Are

We want to be transparent about what we expect from each other. From PURE, you can expect:


Opportunities to stretch and grow: your professional and personal development matters to us. We're committed to providing experiences through on-the-job learning and professional development that increase your impact and rewards.


Clarity and kindness: you can rely on us to be open, honest and supportive, offering clarity on what success looks like.


Support in good times and bad: we believe in showing up for each other consistently, not only when it's easy. You can expect a thoughtful partner, even when we disagree.


A community that cares: we are committed to sustaining a community in which each person feels cared for as an individual. We lift each other up, celebrate wins together and support one another through challenges in work and life.

Who You Are

All of the strongest relationships are a partnership- a two way street. So here's what we ask of you:

  • Aim to bring your best every day: you're here because you want to be part of a team that makes a real impact and aims high.
  • Be a student and a teacher: share your knowledge and talents and be willing to listen and learn from those around you.
  • Get comfortable being uncomfortable: we face tough moments and obstacles with a "courage over comfort" approach and a positive, solutions-oriented mindset.
  • Be a culture builder: building a positive culture is everyone's responsibility, based on care, respect and openness to diverse perspectives.
The base salary for this role can range from $170,000 to $200,000 based on a full-time work schedule. An individual's ultimate compensation will vary depending on job-related skills and experience, geographic location, alignment with market data, and equity among other team members with comparable experience

To ensure a successful onboarding experience, all new hires must work onsite at one of our offices during their first week of employment. Candidates should apply only if they are able to meet this requirement.

Want to Learn More?

  • [Our Values]

  • [Our Benefits]

  • [Our Community Impact]

  • [Our Leadership]