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Data Science Assistant Jobs in Ohio (NOW HIRING)

Further

Data Science Analyst

Cleveland, OH

We are looking for a Data Science Analyst who can not just report on performance, but also ... * Assist in designing and executing reporting, analytics, and optimization briefs. * Partner ...

Radiance Technologies

Data Scientist

Beavercreek, OH

Utilize advanced data science methods to analyze and exploit GEOINT data and other sources of supplementary data to support intelligence production * Assist in developing approaches to address key ...

Radiance Technologies

Data Scientist

Beavercreek, OH · On-site

Utilize advanced data science methods to analyze and exploit GEOINT data and other sources of supplementary data to support intelligence production * Assist in developing approaches to address key ...

Omya

Data Scientist Fall Co-Op 2026

Cincinnati, OH · On-site

... Assist in developing and deploying machine learning models. • Create dashboards and ... data science tools and techniques. Qualifications : Required : • Currently enrolled in an ...

OCLC, Inc.

Senior Data Scientist

Dublin, OH · On-site

Maintain engagement with the data science community and current industry developments to assist in driving technical data science team vision and strategy Requirements: * Master's Degree in a ...

Booz Allen Hamilton

Data Scientist

Beavercreek, OH

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with ...

Flexjet

Senior Data Scientist

Cleveland, OH

... knowledge assistants, document processing systems, and workflow automation tools. The ideal ... computer science, Information Technology, Data Science, or a related field, or an equivalent ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

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 the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
What are the most commonly searched types of Data Science jobs in Ohio? The most popular types of Data Science jobs in Ohio are:
What are popular job titles related to Data Science Assistant jobs in Ohio? For Data Science Assistant jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in Ohio look for? The top searched job categories for Data Science Assistant jobs in Ohio are:
What cities in Ohio are hiring for Data Science Assistant jobs? Cities in Ohio with the most Data Science Assistant job openings:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in Ohio as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.
Data Science Analyst

Data Science Analyst

Further

Cleveland, OH

Full-time

Posted 23 days ago

Job description

WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.

Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients. If this sounds exciting to you, let's chat!

We are looking for a Data Science Analyst who can not just report on performance, but also interpret data to drive decision-making to ensure our clients turn raw data into measurable business value.

What you bring:

  • 2–5 years of professional experience in data science or advanced marketing analytics. We value a background that combines marketing domain expertise with technical data science rigor.
  • Strong command of R and/or Python for data manipulation and statistical analysis.
  • Deep understanding of statistical theory, including hypothesis testing, regression analysis, and experimental design. Familiarity with causal inference methods is a significant plus.
  • Ability to manage client expectations, present to non-technical audiences, and pivot quickly based on evolving business needs.
  • Bonus Points: Proficiency in SQL is preferred for querying data across various cloud warehouses (BigQuery, Snowflake, etc.).
  • Bonus Points: Exceptional "data-to-story" skills—the ability to explain the "so what" behind a coefficient or a p-value.
  • Bonus Points: Adobe Analytics

What you'll be doing:

  • Support discovery work to understand client challenges and develop a structured backlog of evidence-based hypotheses for testing and analysis.
  • Assist in designing and executing reporting, analytics, and optimization briefs.
  • Partner closely with engineers to ensure data accuracy and data pipelines are quality-checked before being leveraged for reporting, analysis or modeling.
  • Perform analysis to uncover actionable insights and develop data-driven recommendations
  • Present findings to internal and client stakeholders in a clear, business-focused way.

What you'll need to accomplish in your first year:

  • Contribute consistently to the experimentation backlog through research, structured hypothesis development, and KPI alignment.
  • Deliver clear, actionable insights from analysis and test results that help clients make confident, data-driven decisions.

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.

Apply today or check out all our opportunities!

By submitting your application, you consent to our collection, processing and disclosure of the contained personal data in accordance with our data practices. If you are a resident of the U.S. state of California, you can read about our data practices and your related privacy rights here. If you are a resident of the European Economic Area, Switzerland or the United Kingdom, you can read about our data practices and your related privacy rights here.