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Product Data Scientist Jobs (NOW HIRING)

Lead Product Data Scientist

San Francisco, CA · On-site

$186.10 - $300.55/hr

BA/BS degree in a quantitative field (e.g., Statistics, Math, CS, Economics) or equivalent practical experience * 12+ years of experience in product analytics or data science within a SaaS/Cloud ...

BA/BS degree in a quantitative field (e.g., Statistics, Math, CS, Economics) or equivalent practical experience * 12+ years of experience in product analytics or data science within a SaaS/Cloud ...

$150 - $210/hr

Product Data Scientist (Product Analytics / ML) Full-Time, Bay Area, Hybrid Location: Bay Area / Hybrid Type: Full-Time Level: Senior / Staff Why this role is exciting Build the feedback system that ...

Data Scientist, Product

San Francisco, CA · On-site

$155K - $260K/yr

Role Overview As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner ...

Data Scientist, Product

Manhattan, NY · On-site

$179 - $210/hr

As a Senior Data Scientist on the Data Science team, you'll be part of a high-impact, multi-functional group working closely with partners across product, engineering, user research, design ...

Data Scientist (Product)

Manhattan, NY · On-site

$100 - $250/hr

At Kalshi, Data Scientists sit at the center of the company and are embedded across Product, Finance, Marketing, Platform, and more. You'll combine analytical depth, technical skill, and business ...

As a Data Scientist, you will play a pivotal role in harnessing data to drive strategic decision-making processes and enhance our product offerings. You will work within a collaborative, innovative ...

We work closely with partners in Product, Paid Media, and Lifecycle Marketing to improve how we acquire users, keep them engaged, and grow their value over time. As a Senior Data Scientist, Product ...

Data Scientist, Product

Seattle, WA · On-site

$230K - $385K/yr

About the Role As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as ...

Showing results 21-40

Product Data Scientist information

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$243.5K

How much do product data scientist jobs pay per year?

As of Sep 5, 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 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 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.

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.

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.
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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 76% Full Time, 5% Part Time, and 19% Contract. Highlights an 83% In-person, 5% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Staff Product Data Scientist, Lending

Block

New York, NY • On-site, Remote

Full-time

Re-posted 15 days ago


Block rating

7.9

Company rating: 7.9 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

9th of 21 rated payment service providers


Job description

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

The Data Science team at Block turns unique customer and product data into decisions that expand access to financial services. Our Lending team powers decisioning behind Cash App Borrow, Afterpay, Square Loans, and the next generation of first-party credit products.

We're looking for a Product Data Scientist to help build, measure, and improve credit products that serve customers traditional credit systems often miss. You'll partner closely with product, engineering, and risk teams to define metrics, evaluate experiments, understand customer behavior, and turn ambiguous product questions into clear decisions.

This is an agentic data science role. You'll use AI tools and agent workflows to move faster and think more rigorously across the full data science loop: exploring messy datasets, building pipelines, stress-testing hypotheses, evaluating product changes, and turning analysis into decisions.

You Will
  • Turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners
  • Use AI tools and agent workflows to improve both the speed and quality of analytical work, from accelerating exploration and automating repetitive tasks to generating hypotheses and stress-testing conclusions
  • Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support
  • Define and maintain measurement frameworks for credit products, including customer eligibility, repayment behavior, product usage, loss performance, funnel health, and long-term customer outcomes
  • Partner with risk teams to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact
  • Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth
  • Approach ambiguous product and risk questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria
  • Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers
  • Lead technical direction and standards for the Block Data Science team - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others.
  • Drive localized cross-team impact by connecting measurement and insights across Lending products (Borrow, Afterpay, Square Loans) and partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy.
  • Mentor and grow the team by developing junior data scientists, fostering a culture of analytical rigor and psychological safety, and contributing to hiring through interviews and calibrations
You Have
  • A bachelor's degree in statistics, data science, economics, computer science, or a similar quantitative field with 12+ years of experience in a relevant role OR
  • A graduate degree in statistics, data science, economics, computer science, or a similar quantitative field with 6-8+ years of experience in a relevant role
  • Advanced proficiency with SQL and experience building clear, decision-oriented data visualizations
  • Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions
  • Experience using AI tools to improve the speed, quality, and durability of analytical work

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