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Product Data Scientist Jobs (NOW HIRING)

Product Data Scientist \n \n \n \n \n \n We're hiring a Product Data Scientist to own the measurement, experimentation, and analytics that shape both the product experience and how we think about ...

Product Data Scientist

Manhattan, NY · On-site

$106K - $180K/yr

Reporting to the Director of Strategic Insights, the Product Data Scientist will be responsible for analyzing disparate data sources to provide recommendations that guide MCU's member-centric growth ...

Product Data Scientist

New York, NY · On-site

$190K - $200K/yr

Learn more about us at getclair.com/about About the Role As a Product Data Scientist at Clair, you'll own the experimentation and analytics layer that drives our product and underwriting decisions.

As our Product Data Scientist , you'll bring rigorous behavior analysis and predictive modeling to how our apps understand and serve our members -- partnering closely with Product and Finance to turn ...

Product Data Scientist We're hiring a Product Data Scientist to own the measurement, experimentation, and analytics that shape both the product experience and how we think about credit and risk. You ...

Product Data Scientist

Denver, CO · On-site +1

$100K - $140K/yr

Product Data Scientist Department: Data Engineering Employment Type: Permanent - Full Time Location: Remote USA - In Tandem Compensation: $100,000 - $140,000 / year Description At In Tandem, we build ...

As our Product Data Scientist , you'll bring rigorous behavior analysis and predictive modeling to how our apps understand and serve our members - partnering closely with Product and Finance to turn ...

As our Product Data Scientist , you'll bring rigorous behavior analysis and predictive modeling to how our apps understand and serve our members - partnering closely with Product and Finance to turn ...

AlphaSense is seeking a highly analytical, entrepreneurial Sr. Product Data Scientist to serve as the analytical engine for our Product Management team and own our most important product analytics ...

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Product Data Scientist information

See salary details

$46K

$165K

$243.5K

How much do product data scientist jobs pay per year?

As of Aug 6, 2026, the average yearly pay for product data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are typical daily responsibilities for a product data scientist?

Product Data Scientists often spend their days analyzing user behavior data, designing experiments such as A/B tests, and developing predictive models to inform product decisions. They collaborate closely with product managers, engineers, and designers to translate data insights into actionable recommendations that improve the product experience. Additionally, they present findings to stakeholders, monitor product metrics, and iterate on analyses as new data becomes available. This dynamic role requires both technical rigor and strong communication to drive data-informed strategies across product teams.

Is a product data scientist still in demand?

Product data scientists are currently in high demand as companies rely on data-driven decision-making to improve products and user experiences. Skills in machine learning, statistical analysis, and tools like SQL and Python are highly valued in this role across various industries.

What is the difference between a data scientist and a product data scientist?

A product data scientist specializes in analyzing data related to a company's products, focusing on improving user experience, product features, and business outcomes. While a general data scientist may work across various domains, a product data scientist often collaborates closely with product teams and uses tools like SQL, Python, and analytics platforms to inform product decisions.

What does a product data scientist do?

A product data scientist analyzes data related to a company's products to improve user experience, optimize features, and drive business decisions. They use statistical methods, machine learning, and data visualization tools to interpret large datasets and provide actionable insights. Strong programming skills in languages like Python or R and knowledge of product metrics are essential for this role.

What is a product data scientist?

A Product Data Scientist focuses on using data to analyze and improve a product’s performance, user experience, and business impact. They work closely with product managers, engineers, and designers to generate insights that drive product decisions. Their responsibilities often include A/B testing, user behavior analysis, and developing data-driven recommendations to enhance user engagement and retention. This role requires strong analytical skills, proficiency in statistical methods, and expertise in data tools like SQL and Python.

What are the key skills and qualifications needed to thrive in the product data scientist position, and why are they important?

To thrive as a Product Data Scientist, you need strong skills in data analysis, statistical modeling, and a deep understanding of product lifecycle metrics, usually supported by a degree in data science, statistics, or a related field. Familiarity with tools such as Python, SQL, Tableau, and advanced analytics platforms, as well as experience with A/B testing frameworks, is highly valued. Excellent communication, business acumen, and cross-functional teamwork are essential soft skills in this role. These capabilities enable data-driven decision-making and ensure that product development initiatives are optimized for user engagement and business impact.

More about Product Data Scientist jobs
What cities are hiring for Product Data Scientist jobs? Cities with the most Product Data Scientist job openings:
What are the most commonly searched types of Product Data Scientist jobs? The most popular types of Product Data Scientist jobs are:
What states have the most Product Data Scientist jobs? States with the most job openings for Product Data Scientist jobs include:
Infographic showing various Product Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Product Data Scientist

ZAP Surgical Systems, Inc.

San Carlos, CA • On-site

Other

Posted 26 days ago


Job description

About the role

No scalpel. No blood. No hospital bunker. The ZAP-X treats tumors and other conditions deep in the brain with a self-shielding gyroscopic robot that steers radiation around the head to sub-millimeter precision — built to put world-class radiosurgery within reach of patients everywhere, not just a handful of elite centers. You’ll join our Product team as a hands-on data scientist, working closely with the Director of Product Management to turn data from our global fleet — treatment plans, delivery and imaging data, system telemetry, and quality records — into models, analyses, and insights that shape what we build. It’s a build-heavy role with room to grow: real modeling problems, direct mentorship, and a front-row seat to how AI is reshaping radiosurgery. You’ll work across software, clinical, quality, and service teams.


What you’ll do

  • Shape the future of AI-assisted treatment planning and delivery. Working closely with the Director of Product Management, you’ll evaluate how AI capabilities — built in-house or brought in through partners — perform on real cases, building the baselines and benchmarks behind the call and helping define what “good enough” looks like. Engineering builds and runs the production systems; you do the hands-on analysis and modeling behind the direction.
  • Tell the story in our data. Use statistical and causal modeling to turn treatment, outcomes, and fleet data into insights that inform leadership’s decisions — how a new feature changes treatment efficiency or patient outcomes across sites, and how the product is actually used, to help sharpen what we build next.
  • Catch problems early. Build predictive and anomaly-detection models, and the early-warning signals on top of them, that surface reliability and quality issues — and support the quality team’s complaint trending and post-market surveillance — before they escalate into complaints or downtime.
  • Make data self-serve. Build dashboards and AI-assisted tooling so quality, operations, and service teams can investigate issues and answer routine questions for themselves.


Your first 12 months

By the end of your first year, you’ll have:

  • Ramped fast — leaning on AI tools to get up to speed on ZAP’s data and domain in weeks, not months — and shipped your first models into use.
  • Put predictive and anomaly-detection models to work flagging reliability and quality issues early for the service and quality teams.
  • Delivered analyses across product, clinical, and fleet questions that leadership acted on.
  • Helped evaluate at least one AI planning or delivery capability, building the baselines and benchmarks behind the recommendation.
  • Built AI-assisted self-serve tooling that lets other teams query the data directly, not just read static dashboards.
  • Become a go-to person for a meaningful slice of ZAP’s data, on a clear path to broader scope.


What we’re looking for (the essentials)

Typically, around 3 years of data science experience.

  • A Bachelor’s or Master’s in a quantitative field — computer science, statistics, engineering, physics, or similar — or equivalent hands-on experience.
  • Proficient in Python, with a solid grounding in statistics and core ML methods.
  • Hands-on experience building models or analyses end to end — from messy data to a result someone actually used.
  • Clear communication — you can explain a finding to a non-technical audience.
  • Eager to learn the domain and grow into bigger problems.

You don’t need to tick every box below. If you’re strong on the essentials and excited by the mission, we’d like to hear from you.


Nice to have

  • Healthcare, medical-device, or other regulated-industry experience.
  • Experience with time-series, anomaly detection, or causal inference.
  • Familiarity with imaging or computer-vision ML.
  • Comfortable querying data with SQL.
  • Exposure to dashboarding or analytics tooling.

This role could suit someone from a data science, ML, or analytics background who wants to build and grow — we care more about how you think with data than your exact title today.