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Entry Level Product Data Scientist Jobs (NOW HIRING)

Data Scientist

Santa Clara, CA · On-site +1

$170K - $190K/yr

Forward Networks seeks a pragmatic, end-to-end Data Scientist who can operate across the full data ... Own selected production data systems: selection, orchestration, monitoring, and tuning

Data Scientist

Santa Clara, CA · On-site +1

$170K - $190K/yr

Forward Networks seeks a pragmatic, end-to-end Data Scientist who can operate across the full data ... Own selected production data systems: selection, orchestration, monitoring, and tuning

Data Scientist

Santa Clara, CA · On-site

$170K - $190K/yr

Forward Networks seeks a pragmatic, end-to-end Data Scientist who can operate across the full data ... Own selected production data systems: selection, orchestration, monitoring, and tuning

Learn GTI's production data stack (Snowflake, dbt, Dagster) and the curated data models that ... data science, quantitative analyst, or ML engineering role - with demonstrable work in model ...

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Every day, millions of scientists rely on our products to discover evidence, connect ideas, validate findings, and advance research. As a Data Scientist, your work will directly contribute to the ...

Data Scientist

Philadelphia, PA · On-site

$103K - $173K/yr

Every day, millions of scientists rely on our products to discover evidence, connect ideas, validate findings, and advance research. As a Data Scientist, your work will directly contribute to the ...

Learn GTI's production data stack (Snowflake, dbt, Dagster) and the curated data models that ... data science, quantitative analyst, or ML engineering role - with demonstrable work in model ...

Data Scientist

Irving, TX · On-site

$65 - $70/hr

We are currently seeking a Data Scientist for our client in the Retail domain. We value our ... and product decisions. This role is ideal for someone who enjoys combining statistical rigor ...

Data Scientist - NYC

Boston, MA · On-site

$100 - $200/hr

Experience with machine learning or adjacent fields (natural language processing, random forests, linear regression, predictive modeling, and entry-level data science concepts) * Experience writing ...

Data Scientist

Boston, MA

$160K - $180K/yr

Data Scientist Company Description Newton Research is a fast-growing software start-up founded by ... Our products to generate actionable business insights for our customers and partners, assisting in ...

Every day, millions of scientists rely on our products to discover evidence, connect ideas, validate findings, and advance research. As a Data Scientist, your work will directly contribute to the ...

Every day, millions of scientists rely on our products to discover evidence, connect ideas, validate findings, and advance research. As a Data Scientist, your work will directly contribute to the ...

The carrier network product group consists primarily of products and solutions for optical-based ... Role Purpose As a Data Scientist, you will serve as a hands-on applied data science contributor ...

Data Scientist

Irving, TX · On-site

$65 - $70/hr

We are currently seeking a Data Scientist for our client in the Retail domain. We value our ... and product decisions. This role is ideal for someone who enjoys combining statistical rigor ...

Learn GTI's production data stack (Snowflake, dbt, Dagster) and the curated data models that ... data science, quantitative analyst, or ML engineering role - with demonstrable work in model ...

Role This role is for a Data Scientist on a close-knit team supporting Air Force Special Operations ... Perform statistical modeling and create data visualizations using products like Tableau, Microsoft ...

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Showing results 1-20

Entry Level Product Data Scientist information

See salary details

$46K

$165K

$243.5K

How much do entry level product data scientist jobs pay per year?

As of Jul 6, 2026, the average yearly pay for entry level 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 the difference between Entry Level Product Data Scientist vs Data Analyst?

AspectEntry Level Product Data ScientistData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; some roles prefer internships or certificationsBachelor's in Statistics, Mathematics, or related field; certifications like Microsoft Excel or SQL are common
Work EnvironmentCollaborates with product teams, engineers, and designers to analyze product data and inform decisionsWorks across departments to interpret data, generate reports, and support business insights
Employer & Industry UsageTech companies, e-commerce, SaaS, and startups focusing on product developmentRetail, finance, healthcare, and various industries requiring data interpretation

While both roles analyze data, Entry Level Product Data Scientists focus on product-related insights and work closely with product teams, whereas Data Analysts handle broader data interpretation across various business functions. The roles often overlap in skills and tools but differ in their primary focus and collaboration scope.

More about Entry Level Product Data Scientist jobs
What cities are hiring for Entry Level Product Data Scientist jobs? Cities with the most Entry Level 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 Entry Level Product Data Scientist jobs? States with the most job openings for Entry Level Product Data Scientist jobs include:

Full-time

Posted 18 days ago


Job description

Roles and Responsibilities
  • Design, develop, deploy, and monitor scalable data science and machine learning solutions in production environments.
  • Build and maintain robust data pipelines supporting data ingestion, transformation, feature engineering, and model deployment.
  • Leverage Snowflake for data engineering, analytics, model integration, and operationalization of data products.
  • Develop predictive models, statistical analyses, and machine learning algorithms using Python and relevant data science libraries.
  • Write, optimize, and maintain complex SQL queries to support analytics, reporting, and model development.
  • Work across the full data science lifecycle, including data acquisition, exploration, modeling, validation, deployment, monitoring, and continuous improvement.
  • Collaborate with business stakeholders, product teams, and engineering teams to translate business requirements into analytical and machine learning solutions.
  • Communicate technical findings, recommendations, and business impact effectively to both technical and non-technical audiences.
  • Ensure data quality, model performance, and operational reliability through ongoing monitoring and governance practices.
Required Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
  • Strong hands-on experience with Snowflake, including solution development, deployment, optimization, and monitoring.
  • Advanced proficiency in Python, including experience with pandas, scikit-learn, and machine learning pipeline development.
  • Strong SQL expertise with the ability to write and optimize complex, high-performance queries.
  • Demonstrated experience building, deploying, and maintaining production-grade data science and machine learning solutions.
  • Experience working across the complete data science lifecycle from data ingestion through deployment and monitoring.
  • Strong analytical, problem-solving, and communication skills with the ability to clearly articulate technical solutions and business outcomes.
Preferred Qualifications
  • Experience with Snowpark (Python and/or Snowpark ML).
  • Exposure to Streamlit, Dash, or similar frameworks for developing data applications and analytical tools.
  • Experience working with both structured and semi-structured datasets.
  • Background in healthcare, life sciences, financial services, or other regulated industries.
  • Experience building internal-facing tools, applications, dashboards, or self-service analytics solutions used by business stakeholders.
  • Familiarity with MLOps, model monitoring, CI/CD pipelines, and cloud-based data platforms.