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Data Science Assistant Jobs in Ohio (NOW HIRING)

Further

Data Science Analyst

Cleveland, OH · On-site

They are seeking a Data Science Analyst who can interpret data to drive decision-making and ensure ... Assist in designing and executing reporting, analytics, and optimization briefs. • Partner ...

Further

Data Science Analyst

Cleveland, OH · On-site

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 ...

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 · On-site

$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 ...

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 ...

Booz Allen Hamilton

Data Scientist

Beavercreek, OH · On-site

$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 ...

Kiva Design

Data Analyst

Cincinnati, OH

Identify potential applications fro data science techniques * Assist management in setting priorities for near-term projects * Drive the collection of new data and the manipulation/refinement of ...

Kiva Design

Data Analyst

Cincinnati, OH · On-site

Identify potential applications fro data science techniques * Assist management in setting priorities for near-term projects * Drive the collection of new data and the manipulation/refinement of ...

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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 June 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Science Analyst

Data Science Analyst

Further

Cleveland, OH • On-site

Full-time

Posted 2 days ago

Job description

Job Summary:
Further is a data, cloud, and AI company focused on helping businesses turn raw data into meaningful decisions. They are seeking a Data Science Analyst who can interpret data to drive decision-making and ensure clients derive measurable business value from their data.
Responsibilities:
• 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.
Qualifications:
Required:
• 2–5 years of professional experience in data science or advanced marketing analytics.
• 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.
• Ability to manage client expectations, present to non-technical audiences, and pivot quickly based on evolving business needs.
Preferred:
• Proficiency in SQL for querying data across various cloud warehouses (BigQuery, Snowflake, etc.).
• Exceptional 'data-to-story' skills—the ability to explain the 'so what' behind a coefficient or a p-value.
• Adobe Analytics
Company:
Further is a data, cloud, and AI company whose sole focus is helping you turn raw data into the right decisions. Founded in 2004, the company is headquartered in Atlanta, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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