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Data Scientist Jobs in Springfield, OH (NOW HIRING)

CareSource

Data Scientist II

Dayton, OH · On-site

$83K - $132K/yr

The Data Scientist II is responsible for designing and validating predictive models, machine learning models, and artificial intelligence that inform and improve business processes across the ...

Munich RE

Actuarial Data Scientist (FCAS)

Dayton, OH · On-site

We are looking for an FCAS to join the American Modern Predictive Analytics team as a Principal Data Scientist and play a key leadership role in advancing pricing model strategy. American Modern ...

HumanIT Solutions

Senior Data Scientist

Beavercreek, OH · Remote

You are a highly motivated Sr. Data Scientist with advanced technical expertise in designing, modernizing, and managing enterprise data environments. You will guide the organization through business ...

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Showing results 21-40

All JobsData Scientist JobsData Scientist Jobs in Springfield, OH

Data Scientist information

See Springfield, OH salary details

$33.8K

$110.6K

$177K

How much do data scientist jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data scientist in Springfield, OH is $110,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,700.00 and $122,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks, data visualization tools, and big data platforms like TensorFlow, Tableau, and Hadoop, as well as certifications in data science, are highly valued. Excellent problem-solving skills, curiosity, and the ability to communicate complex findings clearly set outstanding data scientists apart. These skills and qualities are crucial for extracting actionable insights from data, driving business decisions, and collaborating effectively with stakeholders.

What do data scientists do?

Data scientists collect, confirm, and interpret data to determine useful information for their employer. They help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information data scientists get from the records they gather helps businesses make major decisions in critical areas, such as product development, sales and marketing techniques, and client retention. Data scientists are highly educated; the majority of them have at least a master's degrees, and many have doctorates. Data scientists are valuable members of organizations in many different industries, including pharmaceuticals, manufacturing, and banking.

What are some typical projects data scientists work on, and how do they collaborate with other teams?

Data Scientists often work on projects such as building predictive models, analyzing large datasets to uncover trends, and developing data-driven solutions to business problems. They regularly collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to ensure that their insights are actionable and aligned with business goals. Effective communication and teamwork are essential, as Data Scientists frequently need to present complex findings to non-technical stakeholders and incorporate feedback from various departments.

What is the difference between Data Scientist vs Data Analyst?

AspectData Scientist
Required CredentialsDegree in Computer Science, Statistics, or related field; often requires advanced degrees
Work EnvironmentResearch and development, predictive modeling, machine learning projects
Employer & Industry UsageTech companies, finance, healthcare, consulting firms
Common Search & ComparisonOften compared due to overlapping skills in data analysis and modeling

Data Scientists focus on building predictive models, advanced analytics, and machine learning, often requiring higher-level technical skills and education. Data Analysts primarily interpret existing data, generate reports, and support decision-making with descriptive analytics. While both roles analyze data, Data Scientists handle complex modeling and predictive tasks, whereas Data Analysts focus on data interpretation and reporting.

Is a data scientist job still in demand?

Yes, data scientist roles remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in machine learning, statistical analysis, and programming languages like Python or R are highly valued, and employment opportunities continue to grow as organizations seek to leverage big data for competitive advantage.

What does a data scientist do exactly?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use statistical techniques, programming languages like Python or R, and tools such as SQL and machine learning algorithms to interpret data and solve complex problems.
More about Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in Springfield, OH?

The most popular types of Data Scientist jobs in Springfield, OH are:

What are popular job titles related to Data Scientist jobs in Springfield, OH?

For Data Scientist jobs in Springfield, OH, the most frequently searched job titles are:

What cities near Springfield, OH are hiring for Data Scientist jobs?

Cities near Springfield, OH with the most Data Scientist job openings:

Data Scientist jobs near you
Infographic showing various Data Scientist job openings in Springfield, OH as of August 2026, with employment types broken down into 82% Full Time, 11% Part Time, and 7% Contract. Highlights an 85% In-person, 5% Hybrid, and 10% Remote job distribution, with an average salary of $110,556 per year, or $53.2 per hour.

Data Scientist - Expert - #914

Allen Integrated Solutions

Dayton, OH • On-site

Full-time

Posted 6 days ago

Job description

Data Scientist - Expert - #914

Clearance Required:  TS/SCI 

Dayton, Ohio - 100% onsite

 

Position Overview 

The Expert Data Scientist serves as the principal technical authority and strategic advisor for data science, artificial intelligence, and advanced analytics across the contract in direct support of the National Air and Space Intelligence Center (NASIC). Operating on-site within the NASIC Future Capabilities & Assessment Directorate (NASIC/A9), specifically supporting the Technology, Data, and Assessment Division (A9A), this role leads the design and implementation of next-generation analytical capabilities. 

The Expert Data Scientist pioneers enterprise-wide Intelligent Automation, Artificial Intelligence, and Machine Learning (IA/AI/ML) workflow strategies against highly complex, large-scale datasets. By bridging the gap between cutting-edge computational technology and intelligence operations, this position drives data-driven decisions, guides future enterprise architecture investments, and accelerates critical analytical priorities across the Center, Department of Defense (DoD), and Intelligence Community (IC). 

Core Responsibilities 

  • Strategic AI/ML & Analytical Architecture: Designs, shapes, and leads the implementation of enterprise-wide analytic strategies and next-generation IA/AI/ML techniques. Evaluates emerging commercial cloud capabilities, pilots advanced computational models, and directs technology scouting initiatives to modernize NASIC's digital landscape. 
  • Workflow Optimization & Insight Generation: Translates highly complex, multi-dimensional data science capabilities into clear, actionable insights and executive-ready dashboards for non-technical stakeholders, Group Commanders, and senior leaders. 
  • Cross-Enterprise Data Strategy & Governance: Formulates robust data strategies, metadata governance frameworks, and data standards that directly align with center-wide IT roadmaps, Zero Trust Architecture (ZTA) principles, and national-level AI policies. 
  • Reporting & Progress Documentation: Authors, reviews, and delivers the formal monthly Data Science & Analytics Progress Report to NASIC/A9 leadership. This deliverable captures rigorous metrics on model implementation and presents validated, decision-ready workflow recommendations. 
  • Strategic Communications & Policy Creation: Spearheads high-level technical policy creation and runs strategic communication initiatives to ensure perfect alignment between technical software factories, IT infrastructure stakeholders, and intelligence production groups. 
  • Enterprise Infrastructure Collaboration: Collaborates with the Chief Data Officer (CDO) and Chief Artificial Intelligence Officer (CAIO) to align advanced analytics workflows with cloud storage migrations, secure cross-domain data flows, and enterprise network design configurations. 

Qualifications & Experience 

Required: 

  • Education & Experience: Bachelor's degree plus 18 years of experience, or a Master's degree plus 15 years of experience in Data Science, Computer Science, Statistics, Advanced Mathematics, Data Engineering, or a closely related computational field. 
  • Advanced AI/ML Leadership: Proven track record of leading multi-disciplinary team-tasks in the development, testing, and deployment of complex IA/AI/ML algorithms, Large Language Models (LLMs), or advanced signal processing architectures independent of supervisory guidance. 
  • DoD/IC Standards Compliance: Direct experience developing analytical data frameworks and engineering artifacts that strictly conform to DoD, IC, and Air Force Enterprise Architecture standards. 
  • Security Clearance: Must possess an active, verified TS/SCI security clearance to provide 100% on-site support inside secure NASIC facilities at Wright-Patterson AFB. 
  • Ecosystem Awareness: Direct technical familiarity with data structures inside Vendor or related vendor ecosystems, or a deep understanding of the NSG Tasking, Processing, Exploitation, and Dissemination (TPED) mission framework. 
  • Cloud Architecture Proficiency: Demonstrated experience working inside the NASIC Unified Cloud (NUC), DAF Cloudworks, or modern commercial cloud platforms utilizing Open Container Initiative standards. 

Desired: 

  • NASIC Experience: NASIC experience highly desired, not mandatory.