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How much do data science trainer jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for data science trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Science Trainer position, and why are they important?

To thrive as a Data Science Trainer, you need a strong background in statistics, machine learning, data analysis, and experience with common programming languages like Python or R, typically supported by a degree in a quantitative field. Familiarity with data visualization tools (e.g., Tableau, Power BI), cloud platforms, and certifications such as the Certified Data Scientist credential are often expected. Excellent communication, presentation, and mentoring skills are vital for explaining complex technical concepts to diverse learners. These abilities are crucial to effectively train others, foster engagement, and ensure learners can practically apply data science skills in real-world scenarios.

What does a typical day look like for a Data Science Trainer?

A typical day for a Data Science Trainer involves developing and delivering instructional materials, conducting interactive training sessions, and providing hands-on guidance to students or professionals at varying skill levels. You’ll often collaborate with curriculum developers, other trainers, and industry experts to keep course content up-to-date and relevant. Trainers also assess learner progress through assignments or projects, offer feedback, and may hold one-on-one mentoring sessions to address individual questions. In addition to technical instruction, you’ll help foster a collaborative learning environment that encourages problem-solving and practical application of data science concepts.

What is a Data Science Trainer job?

A Data Science Trainer is responsible for teaching and mentoring individuals or teams in data science concepts, tools, and techniques. They design and deliver training programs covering topics such as machine learning, data analysis, programming (Python, R), and statistical modeling. Trainers may work for educational institutions, corporate training programs, or independently as consultants. Their goal is to equip learners with practical skills to analyze data, build models, and derive insights for real-world applications. Effective trainers combine technical expertise with strong communication and instructional skills.

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What are the most commonly searched types of Data Science Trainer jobs? The most popular types of Data Science Trainer jobs are:
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Data Science Trainer jobs near you
Infographic showing various Data Science Trainer job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 64% Full Time, 26% Part Time, 1% Temporary, and 7% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.
Director, Data Science: Data Science Tools

Director, Data Science: Data Science Tools

Liberty Mutual

Plano, TX • On-site, Remote

$120K - $257K/yr

Full-time

Posted 9 days ago

Liberty Mutual rating

8.9

Company rating: 8.9 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

46th of 261 rated insurance

Job description


Description

The Data Science Infrastructure organization within USRM is hiring a Senior Technical Professional, Data Scientist to join the Data Science Tools team. This role will focus on improving the end-to-end modeling workflow for USRM Data Science by building internal tools, pipelines, and applications that streamline model development, evaluation, deployment, and iteration. The ideal candidate is highly technical, proactive, and motivated by building systems that help other data scientists work more efficiently.

**Candidates who live within 50 miles of Boston, MA; Portsmouth, NH; Seattle, WA; Columbus, OH; or Plano, TX will follow a hybrid schedule, coming into the office two days per week. Otherwise, this role is remote with occasional travel. **

Responsibilities:

  • Design and build internal tools, pipelines, and applications that improve model development, evaluation, and deployment
  • Own strategy and roadmaps for improving data science workflows and tooling across USRM
  • Design, build, and maintain Python packages used across the organization
  • Evaluate and implement AI agent capabilities in tooling using approaches such as MCP, RAG, PydanticAI, LangChain, or related frameworks
  • Work with workflow and modeling tools such as Luigi, Airflow, Celery, MLflow, H2O, scikit-learn, Optuna, and LightGBM, as well as Python development tools such as Pydantic, FastAPI, uv, ruff, and pytest
  • Promote MLOps and AI agent best practices in collaboration with groups such as Enterprise Data & Data Science
  • Stay current on developments in open-source data science frameworks, MLOps, and agentic coding practices
  • Help shape the direction of the Tools team and contribute to a culture of ownership, collaboration, and continuous improvement

The ideal candidate will have:

  • Professional experience building and maintaining Python-based data science or Machine Learning tooling used by multiple end users or teams
  • Worked with any of the following in a professional setting: Git, Bash/shell scripting, uv, pre-commit, ruff, pytest, or Pydantic
  • Built, deployed, or maintained workflows or pipelines using any of the following: Airflow, Luigi, Celery, Databricks, or MLflow
  • Implemented or supported AI/LLM-based tooling using frameworks such as PydanticAI, LangChain, MCP, or RAG
  • Developed, reviewed, or maintained internal Python packages, APIs, or data science applications using tools such as FastAPI, Streamlit, Dash, NiceGUI, or Plotly
  • Applied agentic AI techniques in day-to-day development and incorporate AI capabilities directly into tools and applications where they create meaningful value for data scientists
Qualifications
  • Broad knowledge of predictive analytic techniques and statistical diagnostics of models.
  • Advanced knowledge of predictive toolset; reflects as expert resource for tool development.
  • Demonstrated ability to exchange ideas and convey complex information clearly and concisely.
  • Ability to establish and build relationships within and outside the organization.
  • Ability to give effective training and presentations to management and other groups.
  • Ability to use results of analysis to persuade team, department management or senior management to a particular course of action.
  • Broad knowledge of business drivers and market context.
  • Has a value driven perspective with regard to understanding of work context and impact.
  • Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of  6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of  8 years of relevant experience.
About Us

Pay Philosophy: The typical starting salary range for this role is determined by a number of factors including skills, experience, education, certifications and location. The full salary range for this role reflects the competitive labor market value for all employees in these positions across the national market and provides an opportunity to progress as employees grow and develop within the role. Some roles at Liberty Mutual have a corresponding compensation plan which may include commission and/or bonus earnings at rates that vary based on multiple factors set forth in the compensation plan for the role.
At Liberty Mutual, our goal is to create a workplace where everyone feels valued, supported, and can thrive. We build an environment that welcomes a wide range of perspectives and experiences, with inclusion embedded in every aspect of our culture and reflected in everyday interactions. This comes to life through comprehensive benefits, workplace flexibility, professional development opportunities, and a host of opportunities provided through our Employee Resource Groups. Each employee plays a role in creating our inclusive culture, which supports every individual to do their best work. Together, we cultivate a community where everyone can make a meaningful impact for our business, our customers, and the communities we serve.
We value your hard work, integrity and commitment to make things better, and we put people first by offering you benefits that support your life and well-being. To learn more about our benefit offerings please visit: https://LMI.co/Benefits
Liberty Mutual is an equal opportunity employer. We will not tolerate discrimination on the basis of race, color, national origin, sex, sexual orientation, gender identity, religion, age, disability, veteran's status, pregnancy, genetic information or on any basis prohibited by federal, state or local law.
Fair Chance Notices

  • California
  • Los Angeles Incorporated
  • Los Angeles Unincorporated
  • Philadelphia
  • San Francisco

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About Liberty Mutual

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Since 1912, we've grown into the fifth largest global property and casualty insurer based on 2022 gross written premium. We also rank 86 on the Fortune 100 list of largest corporations in the US based on 2022 revenue. ​At Liberty Mutual Insurance we work hard every day to support our customers and our people, so they can protect their families, build their businesses and invest in their futures. We are headquartered in Boston, but our people, our customers and our reach span the globe. So to better serve our global customers and employees, we are organized into three business units.

Industry

Insurance services

Company size

10,000+ Employees

Headquarters location

Boston, MA, US

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