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Weekend Data Science Jobs in Akron, OH (NOW HIRING)

Design and implement digital engineering infrastructure, leveraging artificial intelligence (AI), machine learning (ML), and data science methodologies to transform large volumes of experimental ...

New

Industry/Sector Not Applicable Specialism Data Science Management Level Director & Summary The Opportunity As an AI & GenAI Data Scientist-Director, you will leverage advanced technologies and ...

The Opportunity As part of the Operations Consulting team, you will apply advanced data science and machine learning techniques to large-scale claims, clinical, and member data to surface actionable ...

Data Engineer

Cleveland, OH ยท On-site

$110K - $133K/yr

The ideal candidate will work closely with data analysts, data scientists, and software engineers to ensure reliable, high-quality data is available for analytics and business intelligence. Key ...

Data Analyst

Akron, OH ยท On-site

$79K - $139K/yr

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or related field with minimum 4 years of relevant work experience. * Relevant work experience includes ...

Data Analyst

Akron, OH ยท On-site

$79K - $139K/yr

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or related field with minimum 4 years of relevant work experience. * Relevant work experience includes ...

Showing results 21-40

Weekend Data Science information

See Akron, OH salary details

$35.9K

$117.4K

$188K

How much do weekend data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for weekend data science in Akron, OH is $117,423.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,200.00 and $130,100.00 per year, depending on experience, location, and employer.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends if their projects or deadlines require it, but many roles follow a standard weekday schedule. Flexibility depends on the employer, project needs, and whether the position involves on-call or urgent tasks. Typically, data science roles are performed during regular business hours, but some positions may require weekend work for data collection, analysis, or reporting.

What skills and qualifications are needed to thrive as a weekend data scientist?

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 is a weekend data science?

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 challenges do data scientists working on weekends face, 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 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 Akron, OH? The most popular types of Data Science jobs in Akron, OH are:
What are popular job titles related to Weekend Data Science jobs in Akron, OH? For Weekend Data Science jobs in Akron, OH, the most frequently searched job titles are:
What job categories do people searching Weekend Data Science jobs in Akron, OH look for? The top searched job categories for Weekend Data Science jobs in Akron, OH are:
What cities near Akron, OH are hiring for Weekend Data Science jobs? Cities near Akron, OH with the most Weekend Data Science job openings:

Chief Data Officer (Bath Township)

Socket.dev

Bath, OH โ€ข On-site

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Overview

C2 ALASKA, LLC

Dayton, OH

The Chief Data Officer shall provide advanced technical support to the AFRL/RA organization, focusing on the development and implementation of data-driven solutions to enhance research and engineering outcomes. This role supports the Chief Data Officer and AI leadership in designing and implementing digital engineering infrastructure, leveraging artificial intelligence (AI), machine learning (ML), and data science methodologies to transform large volumes of experimental, computational, and historical research data into actionable insights. The position plays a critical role in modernizing how hypersonic test and technical report data is accessed, structured, analyzed, and utilizedโ€”enabling improved research efficiency and innovation across AFRL initiatives.

Responsibilities
  • Support the AFRL/RA team in the collection, storage, management, and retrieval of experimental and computational research data.
  • Develop and implement data-driven solutions to enhance research and engineering outcomes.
  • Support the Chief Data Officer and AI leadership.
  • Design and implement digital engineering infrastructure, leveraging artificial intelligence (AI), machine learning (ML), and data science methodologies to transform large volumes of experimental, computational, and historical research data into actionable insights.
  • Assist in implementing and advancing digital engineering infrastructure aligned with government reference architectures.
  • Apply machine learning and AI-powered data mining techniques to:
    • Identify statistical trends within existing datasets
    • Detect gaps in available data (data paucity)
    • Improve the effectiveness of future experimental and computational efforts
  • Collaborate with AFRL/RA AI leadership to design and develop AI agents capable of:
    • Automating extraction of structured data from unstructured historical data packages
    • Utilizing metadata and technical reports to prioritize relevant information for end users
  • Develop and maintain scalable data structures and workflows that enable seamless:
    • Data integration
    • Analysis
    • Storage and retrieval across multiple platforms
  • Integrate heterogeneous datasets from multiple sources into unified analytical frameworks and modeling environments.
  • Support the creation of digital collaboration tools to:
    • Eliminate data silos
    • Enhance accessibility of structured research data
    • Provide streamlined user interfaces for data interaction
    • Enable transformation of fragmented information into structured, accessible, and analysis-ready datasets.
  • Contribute to model development and data-driven decision support tools for research stakeholders.
  • Other duties as assigned.
Qualifications
  • Master of Arts (MA)/Master of Science (MS) in Science; Engineering, Mathematics, or Statistics.
  • Minimum ten (10) years in data science / OR A-type work.
  • Minimum five (5) experience in designing AI/ML solutions, building data architectures, and creating automation (AI agents).
  • Minimum five (5) years working with large-scale or complex datasets.
  • Minimum five (5) years supporting DoD research programs.
  • Possess and maintain an Active Secret Clearance.
Knowledge, Skills and Abilities
  • Knowledge of machine learning, artificial intelligence, and data science techniques.
  • Ability to design and implement data architectures and workflows aligned with enterprise/government standards.
  • Proficiency in handling structured and unstructured data, including data extraction and transformation.
  • Skilled in integrating heterogeneous data sources into unified systems.
  • Ability to develop and support AI-driven automation tools (e.g., data extraction agents).
  • Possess analytical and problem-solving skills applied to complex research datasets.
  • Possess effective collaboration skills across technical, engineering, and research stakeholders.
  • Possess excellent written and verbal communication skills for technical audiences.
  • Ability to translate complex data into meaningful insights for decision-makers.
  • Demonstrated technical communication skills, including preparation of briefings, technical reports, research papers, and publications.
Experience
  • Experience with high-speed flight vehicle technologies, hypersonics, or advanced aerospace systems Preferred.
  • Experience with digital engineering concepts and frameworks Preferred.
  • Experience working with large, complex, and diverse datasets Preferred.
  • Experience in AI/ML model development, training, or deployment Preferred.
  • Familiarity with generative AI tools and data-driven infrastructure development Preferred.
Physical Demands

The employee will need to be able to perform facility inspections.

While performing the duties of this Job, the employee is regularly required to sit and talk or hear. The employee may use repeated motions that include the arms, wrists, hands and/or fingers. The employee is occasionally required to walk, stand, climb, balance, stoop, kneel, crouch, or crawl. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by this job include close vision.

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