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Data Science Training Jobs in Ohio (NOW HIRING)

Safelite Group

Lead Data Scientist

Columbus, OH

The role owns endtoend data science solutions-from problem framing through production deployment ... training cadences. Expected Work Location (In Office) : It is expected that you will primarily ...

Safelite Group, Inc.

Lead Data Scientist

Columbus, OH · On-site

The role owns end-to-end data science solutions-from problem framing through production deployment ... training cadences. Expected Work Location (In Office) : It is expected that you will primarily ...

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How much do data science training jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data science training in Ohio is $95,051.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,902.00 and $112,437.00 per year, depending on experience, location, and employer.

What is a Data Science Training job?

A Data Science Training job involves teaching and guiding individuals or teams in data science concepts, tools, and techniques. Trainers design curricula, conduct workshops, and provide hands-on experience with programming languages like Python or R, machine learning, and data visualization. They may work for educational institutions, corporate training programs, or independently to upskill professionals. The goal is to equip learners with the skills needed to analyze data, build models, and make data-driven decisions.

What are the typical responsibilities of a professional in Data Science Training?

Individuals in Data Science Training roles are responsible for developing, organizing, and delivering curriculum on topics such as data analysis, machine learning, and data visualization. They often lead workshops, create interactive tutorials, and provide one-on-one guidance to learners from diverse backgrounds. Collaboration with data science teams and subject matter experts to ensure training content is current and industry-relevant is common. Additionally, professionals assess learner progress and adapt materials to continuously improve the educational experience. This role is ideal for those passionate about teaching and staying at the forefront of new data science advancements.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and starting at 40 is not too late. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, along with practical experience. Many professionals transition into data science later in their careers and find opportunities based on their expertise and continuous learning.

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

To excel in Data Science Training roles, you need a solid foundation in data analysis, statistical modeling, and expertise with programming languages like Python or R, often supported by a degree in data science or a related field. Familiarity with tools such as Jupyter Notebooks, SQL, machine learning platforms, and certifications like Google Data Analytics or Microsoft Certified: Data Scientist Associate are highly valued. Excellent communication, patience, and instructional skills help convey complex topics clearly and foster a collaborative learning environment. These combined skills are essential for effectively designing and delivering training that empowers learners to succeed in the rapidly evolving field of data science.

Can I get a data scientist job with no experience?

Entering a data scientist role typically requires relevant skills in programming, statistics, and data analysis, often gained through coursework, projects, or certifications. While some entry-level positions may be available to candidates with minimal experience, most employers prefer candidates with practical experience or a strong portfolio demonstrating their abilities.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

Can I get a job after learning data science?

Data science is a growing field with many job opportunities for those who acquire relevant skills such as programming, statistics, and data analysis tools like Python or R. Completing a data science training program can improve your chances of securing roles such as data analyst or data scientist, but employment also depends on experience, portfolio, and industry demand.
What are the most commonly searched types of Data Science Training jobs in Ohio? The most popular types of Data Science Training jobs in Ohio are:
What are popular job titles related to Data Science Training jobs in Ohio? For Data Science Training jobs in Ohio, the most frequently searched job titles are:
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Data Science Training jobs near you
Scientist- Data Research and Development USA

Scientist- Data Research and Development USA

First Solar

Perrysburg, OH • On-site

Full-time

Re-posted yesterday

First Solar rating

6.8

Company rating: 6.8 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

424th of 528 rated manufacturers

Job description


First Solar reserves the right to offer you a role most applicable to your experience and skillset.
Basic Job Functions:
This position supports large scale statistical experiment design and analysis to evaluate innovative ideas on thin-film processes. You will join many disparate data sources to compile an integrated story of discovery, within and across experiments, projects, and people. You will apply an advanced knowledge of statistics and data science techniques to recognize patterns and create insights in a state-of-the-art R&D solar fabrication facility. Design, develop, and evaluate experimental models that point in the direction of maximum success. Serve as lead statistician for project teams, providing expertise, oversight, and guidance on analysis efforts. Provide support, training, and direction to all Advanced Research Engineers on DOE, statistical analysis, and modeling. Help your colleagues build a world and workplace that is just sustainable, and equitable.
Education/Experience:
  • Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 5 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
  • Master's Degree in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, and 3 years of relevant technical experience or 2 years of experience as an Engineer- Analytics R&D at First Solar.
  • Ph.D. in Computer Science, Information Systems, Engineering, Data Science, or similar technical discipline, without prior technical work experience.
  • Previous R&D, PV, or Semiconductor experience helpful, but not necessary.

Required Skills/Competencies:
  • Deep understanding of Design of Experiments.
  • Meta-analysis and systematic research review.
  • Data forensics and partitioning on large data sets.
  • Data Wrangling: preparation, mapping, and transformation.
  • Structured and unstructured data sets.
  • Executive level storytelling with data visualization.
  • Impart clarity when communicating complex data relationships.
  • Linear Algebra: Matrix Algebra and eigenvalues/vectors.
  • Passion to learn new areas of study (device physics learning will be intensive).
  • High emotional intelligence.
  • Bravery to speak a dissenting opinion or present evidence against current belief.
  • Skilled in a structured problem-solving method (such as DMAIC, A3, 5 Whys, etc.).
  • Extensive understanding of Probability and Inferential Statistics as well as visual display of these concepts.
  • Expert at building predictive models and utilizing advanced statistical analysis, including generalized linear models, decision trees, PCA, logistic and multivariate regression.
  • Deep knowledge of statistical and modeling software tools and scripting languages such as JMP, SAS, Python, SPSS, or R to manipulate data and draw insights from large data sets.
  • Experience with Microsoft environment: Windows OS, Office 365, Teams, SharePoint, etc.

Essential Responsibilities:
  • Development Program Statistical Research & Meta-analysis (70%)
    • While assigned to a Development Program, serve as statistical expert and work with Technical, Operations and Process Engineering Teams to achieve program goals via research, modeling, experiment design and analysis.
    • Gain deep understanding of program objectives, learning the physics behind the processes to know current and predict future Program Team needs.
    • Help Team define an experiment's statement of intent, reviewing previous responses and assuring factor estimability is understood.
    • Systematic review of prior experimentation to find relevant, high-quality data, while accounting for variability in study approach, sample size, execution, environment, etc.
    • Standardize and weight prior research to build new predictive models to guide Program experimentation.
    • Understand experimenter's needs and develop custom experiment design to efficiently create insight.
    • Exhaustively evaluate experiment design and resulting model.
    • Work with Program Partners to define and prepare datasets for modeling.
    • Monitor many data streams and feedback data quality to Program Teams.
    • Be the data forensics Program Lead, data mining root cause of un-intended processing artifacts.
    • Explore data using a variety of statistical (e.g., data mining, regression, cluster analysis, partitioning, PCA) techniques to answer research questions and guide future experiments.
    • Synthesize independent experiment findings into overall treatment effects.
    • Prepare testing scenarios and test model performance against new results, subsets, etc.
    • Clearly and concisely communicate analysis and modeling results to business partners, supporting socialization and adoption of results into business activities and decisions.
    • Perform Program meta-analysis, putting the newest experiment in context with history, highlighting key abnormalities, consistencies, and correlations.

  • Data Science & Statistics Subject Matter Expert (30%)
    • Define data structures and systems that will institutionalize improvements and lower the bar for analysis across the organization.
    • Hone and proliferate the craft of cross-experiment meta-analysis in Research & Development.
    • Assist in development of standard analytical approaches and methodologies for the department.
    • Apply advanced statistical techniques, including analysis of variance, t-tests, factor analysis, regression, multivariate analyses, PCA or simulation, to analyze the effects of experimentation.
    • Provide guidance and direction related to statistical analysis to less experienced Research & Development staff as needed.
    • Provide peer review related to analytics methods and results.
    • Work closely with Development Technical Teams to identify and answer critical questions.
    • Identify and scope new opportunities for statistical analysis applications and scripting.
    • Proactively research and leverage new statistical techniques and technologies to apply and teach.
    • Develop and lead training sessions for advanced Data Science & Statistics concepts.
  • Other duties as assigned.
  • Job description subject to change at any time.

Reporting Relationships:
  • This position will report to the Analytics Manager.
  • This position may have direct reports.

Travel:
  • 0% - 5% (On occasion/as needed for training, etc.)

Estimated Salary Range:
  • $91,200-$130,000 Annually

US Physical Requirements:
  • Will sit, stand or walk short distances for up to the entire duration of a shift.
  • Will climb stairs on an occasional basis.
  • Will lift, push or pull up to 37 pounds on an occasional basis.
  • Required to use hands to grasp, lift, handle, carry or feel objects on a frequent basis.
  • 20/40 vision in both eyes together, with or without correction, is required.
  • Must be able to comply with all safety standards and procedures.
  • May reach above shoulder heights and below the waist on a frequent basis.
  • May stoop, kneel, or bend, on an occasional basis.
  • Ability to wear personal protective equipment is required (including but not limited to; steel-toed shoes, gloves, safety glasses, hearing protection, protective jacket or apron and arm guards, and a condition of employment and continued employment (requires little or no facial hair) for those requiring respirator use.

Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required.
Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.

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