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Product Data Scientist Jobs (NOW HIRING)

MLabs

Staff Product Data Scientist

New York, NY · On-site

Data Scientist Location: New York On-site Full-time Compensation: Competitive Our client is a high ... Partner directly with product and engineering teams to implement data-driven solutions and ensure ...

MLabs

Staff Product Data Scientist

New York, NY · On-site

Data Scientist Location: New York On-site | Full-time Compensation: Competitive Our client is a ... Partner directly with product and engineering teams to implement data-driven solutions and ensure ...

Docusign

Lead Product Data Scientist

San Francisco, CA · On-site

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 ...

MLabs

Staff Product Data Scientist

New York, NY

Data Scientist Location: New York On-site | Full-time Compensation: Competitive Our client is a ... Partner directly with product and engineering teams to implement data-driven solutions and ensure ...

DocuSign

Lead Product Data Scientist

San Francisco, CA · Hybrid

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 ...

Harvey

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 ...

AlphaSense

Sr. Product Data Scientist

Manhattan, NY · On-site

They are looking for a Sr. Product Data Scientist to bridge raw data with strategic product decisions, focusing on deep product analysis and AI-driven data democratization. Responsibilities : • Be ...

AlphaSense

Sr. Product Data Scientist

New York, NY · On-site +1

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 ...

Jobgether

As a Data Scientist focused on Product and Analytics, you will transform complex data into actionable insights that shape product decisions and improve user experiences at scale. Working at the ...

OpenAI

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 ...

Snowflake

Senior Data Scientist - Product

Menlo Park, CA · On-site

$168K - $220K/yr

The Product Data Science team is looking for a Full-stack Senior Data Scientist to come aboard and be part of Snowflake's most critical initiatives. In this role, you will work closely with our ...

Descript

Lead Data Scientist, Product

As a founding product data scientist, you will conduct in-depth analyses to shape product strategies, drive engagement, and enhance the experimentation culture within the company. Responsibilities ...

Hinge Health, Inc

Senior Data Scientist

San Francisco, CA · On-site

$164K - $247K/yr

As we scale this offering, we need a Senior Product Data Scientist to own analytics, experimentation, and measurement across the Visits and Discovery experience. This is a 0-to-1 role. You will be ...

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Product Data Scientist information

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$46K

$165K

$243.5K

How much do product data scientist jobs pay per year?

As of Jul 17, 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 data scientist job still in demand?

Data scientist roles remain in high demand across industries due to the increasing reliance on data-driven decision making. Skills in programming, statistical analysis, and machine learning tools like Python or R are highly valued, and the field continues to grow as organizations seek to leverage big data for competitive advantage.

Is 40 too late for data science?

Product Data Scientists can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or SQL. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

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 data analysis platforms are essential for this role.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Product Data Scientists often use this rule to prioritize data analysis and feature selection, focusing on the most impactful variables to improve model performance efficiently.

What is a Product Data Scientist job?

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.

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Product Data Scientist jobs near you

Staff Product Data Scientist

MLabs

New York, NY • On-site

Full-time

Posted 9 days ago

Job description

Data Scientist
Location: New York
On-site Full-time
Compensation: Competitive
Our client is a high-performance technology development company responsible for the entire technical stack behind the world's largest and most active digital asset launchpads. Operating at the absolute edge of crypto scale, the systems managed by this organization are defined by ultra-low latency, high throughput, and constant high-concurrency load. This is a mission-critical environment where technical precision is paramount and the impact of every deployment is immediate.
The organization is seeking an experienced, versatile Data Scientist who thrives in an intense, fast-paced setting. This role provides the autonomy to identify high-impact opportunities, design sophisticated analytical solutions, and measure their direct effect on a product used by massive global audiences. Joining this team means entering a high-density talent environment that values first-principles thinking, extreme ownership, and the ability to operate independently within a high-stakes ecosystem.
Key Responsibilities
  • Experimentation & Optimization: Design, execute, and analyze rigorous A/B tests to optimize the consumer product experience and drive user engagement.
  • Proactive Analysis: Independently identify hidden problems and growth opportunities through deep-dive data exploration.
  • Insight Visualization: Build and maintain high-fidelity dashboards to track critical KPIs and visualize complex market and user behaviors.
  • Predictive Modeling: Develop sophisticated models to understand user behavior and predict outcomes in a volatile, real-time environment.
  • Cross-Functional Collaboration: Partner directly with product and engineering teams to implement data-driven solutions and ensure technical feasibility.
  • Project Ownership: Drive data initiatives from initial problem identification through to solution implementation and post-deployment measurement.
  • Technical Communication: Translate complex statistical findings into clear, actionable narratives for both technical and non-technical stakeholders.
  • Methodological Standards: Help establish and refine the organization's data best practices and analytical methodologies.

Work Style & Environment
  • In-Person Collaboration: This role is based in-person at our client's office.
  • Intensity: Candidates must be comfortable with unconventional hours and an intense, high-velocity pace where expectations are high and impact is immediate.

Interview Process
  1. Recruiter / HR Call: Initial screen regarding background and professional motivations.
  2. Hiring Manager Interview I: A deep dive into technical skills and past project ownership.
  3. Hiring Manager Interview II: A focused discussion on experimentation, methodology, and problem-solving.
  4. Final Interview: Comprehensive wrap-up focusing on strategic alignment and role expectations.

Requirements
  • Professional Experience: 3+ years of Data Science experience within a startup, high-growth scale-up, or FAANG-tier environment.
  • Technical Stack: Advanced proficiency in Python or R, alongside mastery of SQL (specifically within BigQuery environments).
  • Experimentation Mastery: Strong experience in the end-to-end lifecycle of designing and analyzing A/B tests for high-traffic consumer products.
  • Execution & Agency: Demonstrated ability to work autonomously, managing entire project lifecycles from ideation to implementation without constant oversight.
  • Communication: Exceptional ability to synthesize data insights into actionable business recommendations.

Preferred Qualifications
  • Domain Expertise: Direct experience with cryptocurrency, blockchain data, or fintech/consumer tech products.
  • Advanced Visualization: High-level skills in data visualization tools (e.g., Omni, Looker).
  • Statistical Rigor: Advanced knowledge of causal inference and complex statistical methods.
  • Data Engineering: Experience building and maintaining data pipelines using modern tools such as Dagster or dbt.
  • Machine Learning: Familiarity with ML methods and their practical applications in product environments.

Benefits
  • Unmatched Autonomy: Significant freedom to identify projects and see them through to completion.
  • Scale Exposure: Direct exposure to data systems operating at the frontier of the crypto industry.
  • High Impact: The ability to ship fast and see real-world results from your work within hours or days.
  • Elite Peer Group: Opportunity to collaborate with a mission-driven group of builders who hold a high bar for excellence.
  • Compensation: A competitive package consisting of a Base Salary plus Equity/Tokens.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city.
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd's Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.

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