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Healthcare Data Science Jobs in Ohio (NOW HIRING)

Credence

Data Science Manager

Dayton, OH · On-site

Position Summary Credence has an immediate need for a Data Science Manager at the journeyman level ... Benefits * Health Care Plan (Medical, Dental & Vision) * Retirement Plan (401k, IRA) * Life ...

GRVTY

Data Science - Senior

Dayton, OH · On-site

Advanced degree in Computer Science, Data Science, Electrical Engineering, or related field, or ... health plan including medical, dental, and vision • Health Savings Account with company ...

Credence

Data Science Manager

Dayton, OH · On-site

Position Summary Credence has an immediate need for a Data Science Manager at the journeyman level ... Benefits * Health Care Plan (Medical, Dental & Vision) * Retirement Plan (401k, IRA) * Life ...

EssilorLuxottica

Data Scientist

Mason, OH · On-site

Translate ambiguous business problems into structured data science statements * Organize ... Benefits may include health care, retirement savings, paid time off/vacation, and various employee ...

Essilor

Data Scientist

Mason, OH · On-site

Translate ambiguous business problems into structured data science statements * Organize ... Benefits may include health care, retirement savings, paid time off/vacation, and various employee ...

EssilorLuxottica Group

Data Scientist

Mason, OH · On-site

Translate ambiguous business problems into structured data science statements * Organize ... Benefits may include health care, retirement savings, paid time off/vacation, and various employee ...

Radiance Technologies

Data Scientist

Beavercreek, OH · On-site

Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, educational ... Utilize advanced data science methods to analyze and exploit GEOINT data and other sources of ...

Goosehead

Data Scientist

Westlake, OH

Define and drive the vision for data science at Goosehead, identifying transformative opportunities ... High-quality voluntary health, vision, disability, life, and dental insurance programs * 401K ...

A-TEK Inc.

Health IT Data Engineer

Continental, OH · On-site

$125K - $135K/yr

The successful candidate will work closely with analysts, data scientists, and application teams to ... Power BI and Tableau development experience. * Healthcare data integration experience. * Knowledge ...

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Healthcare Data Science information

What are the key skills and qualifications needed to thrive as a healthcare data scientist?

To thrive as a Healthcare Data Scientist, you need a strong background in statistics, data analysis, programming (Python or R), and an understanding of healthcare systems, often supported by a degree in data science, computer science, or a related field. Experience with tools like SQL, machine learning frameworks, and familiarity with electronic health record (EHR) systems are typically required. Strong problem-solving skills, attention to detail, and effective communication help translate complex data insights into actionable healthcare solutions. These skills are crucial for deriving meaningful insights from complex healthcare data, improving patient outcomes, and supporting evidence-based decision-making.

What is the difference between Healthcare Data Science vs Healthcare Data Analysis?

AspectHealthcare Data ScienceHealthcare Data Analysis
Required CredentialsTypically requires a degree in data science, statistics, or related fields; often includes programming skills and knowledge of machine learningUsually requires a background in healthcare, statistics, or data analysis; may include certifications in data analysis tools
Work EnvironmentInvolves developing models, algorithms, and predictive analytics; often in research or tech-focused settingsFocuses on interpreting data, generating reports, and supporting clinical or administrative decisions
Employer & Industry UsageUsed by healthcare tech companies, research institutions, and large healthcare providersCommon in hospitals, clinics, insurance companies, and healthcare consulting firms

Healthcare Data Science and Healthcare Data Analysis share overlapping skills but differ mainly in scope. Data scientists develop advanced models and predictive tools, while data analysts focus on interpreting data and generating insights. Both roles are vital in healthcare but serve different functions within the industry.

What are some common challenges faced by healthcare data scientists when working with clinical data?

Healthcare data scientists often navigate challenges such as dealing with incomplete or inconsistent medical records, ensuring patient privacy and data security, and integrating data from diverse sources like electronic health records, lab results, and imaging systems. Additionally, they must collaborate closely with clinicians and IT staff to interpret complex datasets accurately and ensure that their analyses have practical clinical value. Maintaining compliance with healthcare regulations, such as HIPAA, is also a critical aspect of the role.

What can you do with a degree in healthcare data science?

A degree in healthcare data science prepares individuals to analyze medical data, develop predictive models, and improve patient outcomes. Graduates can work as data analysts, data scientists, or informaticists in hospitals, healthcare companies, or research institutions, often using tools like Python, R, and SQL. The role involves interpreting complex data to support clinical decisions and healthcare policies.

What is healthcare data science?

Healthcare data science is a field that uses data analysis, statistics, and machine learning to extract insights from health-related data. Professionals in this area work with large datasets from sources like electronic health records, clinical trials, and wearable devices. Their goal is to improve patient outcomes, optimize hospital operations, and support medical research by turning raw data into actionable information. This field requires knowledge of healthcare systems, data management, and advanced analytics techniques.

Can a healthcare data scientist work in healthcare?

Yes, healthcare data scientists work within healthcare organizations to analyze medical data, improve patient outcomes, and optimize operational efficiency. They often use tools like Python, R, and SQL, and require knowledge of healthcare systems, data privacy regulations, and statistical methods.
What are popular job titles related to Healthcare Data Science jobs in Ohio? For Healthcare Data Science jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Healthcare Data Science jobs in Ohio look for? The top searched job categories for Healthcare Data Science jobs in Ohio are:
What cities in Ohio are hiring for Healthcare Data Science jobs? Cities in Ohio with the most Healthcare Data Science job openings:
Healthcare Data Science jobs near you
Infographic showing various Healthcare Data Science job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 9% Part Time, and 6% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Science Manager

Credence

Dayton, OH • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Overview
At Credence, we support our clients' mission-critical needs, powered by technology. We provide cutting-edge solutions, including AI/ML, enterprise modernization, and advanced intelligence capabilities, to the largest defense and health federal organizations. Through partnership and trust, we increase mission success for war-fighters and secure our nation for a better future.
We are privately held, are repeatedly recognized as a top place to work, and have been on the Inc. 5000 Fastest Growing Private Companies list for the last 13 years. We practice servant leadership and believe that by focusing on the success of our clients, team members, and partners, we all achieve greater success.
Position Summary
Credence has an immediate need for a Data Science Manager at the journeyman level to support HQ AFMC A4/10 at Wright Patterson AFB, OH. . This role is ideal for a data professional who enjoys transforming complex procurement, logistics, and enterprise systems data into actionable insights through analytics, automation, dashboards, data modeling, and decision-support solutions for Air Force stakeholders.
The Headquarters Air Force Material Command Directorate of Logistics, Civil Engineering, Force Protection, and Nuclear Integration (HQ AFMC/A4/10) has the AFMC mission responsibility to: shape the workforce and infrastructure to provide logistics, sustainment, and installation support for acquisition logistics, supply management, depot maintenance, and base-level logistics operations, and deliver responsive strategic facility and infrastructure oversight and over-arching direction for all Major Command (MAJCOM) security operations...resulting in war-winning expeditionary capabilities.
In this position, the selected candidate will support enterprise data modernization efforts by helping connect data across systems, improve data quality, identify trends, develop meaningful visualizations, and translate business needs into scalable analytics and business intelligence solutions.
Responsibilities include, but are not limited to the duties listed below:
  • Provide professional services in support of the Digital Materiel Management (DMM) initiative as defined in the PWS.
  • Support DMM modernization efforts by providing integrated tools for contract data normalization, analysis, and analytics to facilitate Air Force-wide insight into procurement data.
  • Utilize current and future DoD and Air Force IT systems to connect procurement data and generate tools and visualizations for the procurement community.
  • Perform professional and administrative tasks in support of the contracting functional community's DMM efforts.
  • Gather business requirements, analyze source systems, define underlying data sources and transformation requirements, design data models, and develop metadata for data analysis and visualization.
  • Acquire and analyze data and metrics across the enterprise to determine how they can be incorporated into data visualizations and dashboards.
  • Conduct exploratory data analysis, trend analysis, and data quality assessments to uncover patterns, risks, opportunities, and actionable insights that support operational and strategic decision-making.
  • Collaborate with business areas and project teams to elicit, identify, prioritize, and document data visualization and business intelligence requirements.
  • Translate complex data findings into clear narratives, dashboards, and data stories that enable non-technical stakeholders to understand key insights and make informed decisions.
  • Serve as a functional and technical data visualization and business intelligence subject matter expert.
  • Translate business analysis and business needs into prototype concepts for reports and dashboards and contribute to design and visualization best practices.
  • Utilize business intelligence tools to take dashboard requirements and develop deliverable solutions.
  • Create and update Python scripts for data translation from multiple sources.
  • Support data pipeline, data integration, and automation activities by working with structured and unstructured data from multiple enterprise systems and applying repeatable, scalable approaches to data transformation.
  • Serve as a functional and technical Robotic Process Automation (RPA) subject matter expert.
  • Document data acquisition, data management, and data governance processes.
  • Promote data governance, metadata management, data lineage, and standardization practices to improve consistency, usability, and trust in enterprise data assets.
  • Make and implement process improvements and efficiencies.
  • Create training materials and user guides.
  • Conduct group and one-on-one training sessions with end users.

Requirements
Education, Requirements and Qualifications:
  • Must have an active or current Secret security clearance, or higher.
  • BA/BS degree and at least three (3) years of experience in the respective technical/professional discipline being performed, with proper certifications required in the labor category performance requirements
  • OR six (6) years of directly related experience.
  • Knowledgeable in enterprise software development and the acquisition life cycle, with applied knowledge of Government program management skills and document preparation.
  • Ability to use Government-provided office automation tools.
  • Knowledge of federal and Department e-business and contracting systems, analytics platforms, and data tools, including but not limited to Conwrite, Automated Contract Preparation System (ACPS), CON-IT, Advana, CDO-VALT, Program Management Resource Tools (PMRT), Federal Procurement Data System-Next Generation (FPDS-NG), Procurement Integrated Enterprise Environment (PIEE) suite, Electronic Document Access (EDA), Wide Area Workflow (WAWF), ABSS, ERP systems, SQL, Python, UiPath, Qlik Sense, QlikView, Tableau, Power BI, Power Apps, and • Power Automate, data modeling, dashboard development, data visualization, data transformation, and business intelligence reporting.
  • Extensive knowledge of the federal acquisition process, including in-depth experience with the Federal Acquisition Regulation (FAR), Defense Federal Acquisition Regulation Supplement (DFARS), Department of the Air Force Federal Acquisition Regulation Supplement (DAFFARS), and DoD and Air Force acquisition instructions.

Preferred Experience:
  • Hands-on experience with Python, SQL, Power BI, Tableau, Qlik, Power Apps, Power Automate, UiPath, or similar tools for dashboards, reporting, automation, and data-driven solutions.
  • Experience leveraging AI/ML, Generative AI, predictive analytics, or automation technologies to improve data-driven decision-making, business process efficiency, and operational outcomes within DoD, Air Force, or federal environments.
  • Experience with data pipelines, integration, transformation, cleansing, validation, data modeling, governance, metadata, or data lineage.
  • Ability to apply exploration analysis, trend analysis, statistical analysis, predictive analytics, or machine learning concepts to support business insights and decision-making.
  • Strong ability to present complex data insights through clear dashboards, visualizations, narratives, and recommendations for technical and non-technical stakeholders.

Benefits
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Short Term & Long Term Disability
  • Training & Development

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