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Weekend Data Science Jobs in Ohio (NOW HIRING)

DataAnnotation

Data Science Consultant

Wyoming, OH · On-site +1

$40/hr

Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills ...

BGI (Ohio)

Computer Science and Data Science

Akron, OH · On-site

General responsibilities in Computer Science include developing and extending software frameworks in enterprise architectures, data interfaces, programing in compiled and interpreted languages, and ...

Further

Data Science Analyst

Cleveland, OH

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.

Sequoia Financial Group Llc

Data Scientist

Dublin, OH · On-site

This hands-on role requires technical depth in Python programming, data science workflows, and a strong understanding of mapping business requirements to data models. The ideal candidate will be ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Lead Data Science Projects * Translate complex business requirements into robust, scalable technical solutions. * Select and implement appropriate modeling techniques, including classical ML, deep ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Lead Data Science Projects * Translate complex business requirements into robust, scalable technical solutions. * Select and implement appropriate modeling techniques, including classical ML, deep ...

Kanak Elite Services Inc

Data Scientist.

Columbus, OH · On-site

Data Science - 7+ yrs * SAS - 5+ * Python -5+ * SQL * Jupyter, Data Robot preferred * AI tools preferred * BS w/financial svcs or auto industry exp. required Required: • Bachelor's degree (Major in ...

Cavaliers Holdings LLC

Data Scientist

Cleveland, OH · On-site

$70K/yr

Maintain an understanding of the latest trends and technologies related to data science. REQUIRED QUALIFICATIONS: * Bachelor's Degree in a quantitative field (Math, Stats, Analytics, Engineering ...

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Weekend Data Science information

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

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What are some typical challenges faced by data scientists working specifically on weekends, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is a Weekend Data Science job?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

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 Weekend Data Science jobs in Ohio? For Weekend Data Science jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Weekend Data Science jobs in Ohio look for? The top searched job categories for Weekend Data Science jobs in Ohio are:
What cities in Ohio are hiring for Weekend Data Science jobs? Cities in Ohio with the most Weekend Data Science job openings:
Weekend Data Science jobs near you
Infographic showing various Weekend Data Science job openings in Ohio as of May 2026, with employment types broken down into 1% As Needed, 69% Full Time, 29% Part Time, and 1% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.
Data Science Consultant

Data Science Consultant

DataAnnotation

Wyoming, OH • On-site, Remote

$40/hr

Full-time

Posted 15 days ago

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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