Data Science Manager Jobs in Indiana
Data Science Manager jobs in Indiana are concentrated in healthcare analytics, financial services, and advanced manufacturing, with strong demand from enterprise technology teams at large regional employers. Indianapolis anchors the market, followed by Fort Wayne and Bloomington, where companies like Eli Lilly, Salesforce, and Indiana University Health maintain substantial data and analytics functions. The most in-demand specialties are machine learning operations, healthcare data strategy, and enterprise analytics leadership. See the openings below and apply to the ones that match your experience.
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Cook Research Incorporated is seeking an innovative and strategic leader to serve as Director of Biostatistics and Clinical Data Science. This leader will provide operational direction for Biostatistics and Clinical Data Science and strategic guidance to the use of Real-World Evidence, Advanced Analytics with Artificial Intelligence, and data-driven decision support capabilities that support global clinical research, regulatory strategy, post-market evidence generation, and product lifecycle management.
The successful candidate will lead multidisciplinary teams responsible for Biostatistics and Clinical Data Science. Technical specialties include biostatistics, data engineering, advanced analytics, and emerging AI-enabled capabilities. This role sits within the clinical research arm of Cook Medical and will partner extensively with Regulatory Affairs, HEOR, R&D, Product Management, IT, executive leadership, and others to transform data into evidence, insights, and innovation.
Biostatistics and Clinical Data Science Leadership
- Provide leadership and strategic direction for Biostatistics and Clinical Data Science teams.
- Guide statistical strategy for clinical studies, registries, post-market surveillance programs, and evidence-generation initiatives.
- Ensure scientific rigor and technical excellence in study design, analysis, interpretation, and communication of clinical evidence.
- Oversee development and implementation of analytical standards, methodologies, and best practices.
Real-World Data and Evidence Strategy
- Lead development and execution of real-world data (RWD) and real-world evidence (RWE) strategies.
- Evaluate opportunities to leverage internal and external data sources for evidence generation.
- Support regulatory, reimbursement, health economics, scientific publication, and business decision-making needs through innovative evidence approaches.
- Collaborate across functions to identify and address evidence gaps throughout the product lifecycle.
Artificial Intelligence and Digital Transformation
- Identify and prioritize opportunities to leverage artificial intelligence and advanced analytics techniques.
- Guide responsible and ethical adoption of AI-enabled workflows that improve productivity, decision support, and evidence generation.
- Establish governance that ensure appropriate risk management, transparency, quality, and regulatory compliance.
- Promote an understanding and adoption of AI technologies.
Data Platform Strategy
- Provide leadership for development and adoption of enterprise analytics and data platform capabilities.
- Support data integration, scalable analytics workflows, knowledge management, and self-service analytics solutions.
- Sponsor high-value analytical and AI proof-of-concept initiatives.
- Improve accessibility and usability of research, clinical, and operational data assets.
Organizational Leadership
- Lead, mentor, and develop managers and technical professionals.
- Build organizational capability through workforce planning, talent development, succession planning, and recruiting.
- Allocate resources effectively across a diverse portfolio of clinical, regulatory, analytics, and innovation initiatives.
- Foster a culture of scientific rigor, collaboration, innovation, quality, and continuous improvement.
Cross-Functional Leadership
- Serve as a strategic advisor to Clinical Affairs and organizational leadership.
- Partner with Regulatory Affairs, HEOR, R&D, Quality, Product Management, and IT leaders.
- Represent the organization in scientific, regulatory, academic, and industry collaborations.
- Influence organizational strategy through data-driven decision making and evidence-based recommendations.
Education
PhD required in one of the following disciplines:
- Biostatistics
- Statistics
- Epidemiology
- Data Science
- Biomedical Informatics
- Computational Biology
- Computer Science (with significant healthcare or clinical analytics experience)
- Biomedical Engineering (with significant quantitative research experience)
- Related quantitative discipline
Experience
- Minimum 10 years of progressive experience in clinical research, biostatistics, clinical data science, epidemiology, real-world evidence, advanced analytics, or related fields.
- Demonstrated experience leading multidisciplinary technical teams.
- Experience supporting clinical research and evidence-generation programs in regulated healthcare environments.
Technical Expertise
Candidates should possess significant experience in several of the following areas:
- Clinical study design and statistical methodology
- Clinical research and medical device development
- Regulatory evidence generation
- Real-world data and real-world evidence
- Data science and advanced analytics
- Data governance and quality systems
- Artificial intelligence and machine learning applications
- Analytics platforms and modern data ecosystems
- Scientific publication and presentation activities
Preferred Qualifications
- Experience within the medical device industry.
- Experience interacting with FDA, notified bodies, PMDA, NMPA, or other global regulatory authorities.
- Experience developing RWD/RWE programs.
- Experience with AI governance and implementation in regulated environments.
- Experience leading organizational or digital transformation initiatives.
- Record of scientific publications, conference presentations, or broader professional engagement.
- Experience collaborating with academic institutions, registries, healthcare systems, or external research partners.
What Success Looks Like
- Provide clear vision and leadership for Biostatistics and Clinical Data Science teams.
- Advance Cook's capabilities in evidence generation and analytics.
- Expand the effective use of real-world data and real-world evidence.
- Enable responsible adoption of artificial intelligence and advanced analytics.
- Strengthen enterprise data and analytics capabilities.
- Build and develop high-performing technical teams.
- Serve as a trusted strategic advisor across Clinical Affairs and the broader organization.
See All 6 Data Science Manager Jobs in Indiana
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Find Data Science Manager JobsData Science Manager Jobs by City in Indiana
Where Indiana roles are concentrated, by current openings.
Data Science Manager Job Market in Indiana
A snapshot from current Indiana openings, updated as new roles post.
Who's Hiring



What Indiana Employers Look For
The qualifications that appear most often in data science manager jobs across Indiana.
- Bachelor's or master's degree in data science, statistics, computer science, or a related field
- Five or more years of experience in data science or analytics roles
- Demonstrated experience leading and mentoring data science or analytics teams
- Proficiency in Python, R, SQL, and modern machine learning frameworks
- Experience translating business problems into data-driven solutions for stakeholders
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud
Data Science Manager Jobs in Indiana: Frequently Asked Questions
How do you become a data science manager in Indiana?
The path typically starts with a bachelor's degree in a quantitative field and several years of hands-on data science work before moving into a management role. Indiana does not require a state-issued license for data science managers, so hiring decisions focus on technical depth, leadership experience, and domain knowledge. Advanced degrees or professional certifications in data science, machine learning, or business analytics strengthen candidacy at major Indiana employers in healthcare, finance, and manufacturing.
Which companies hire data science managers in Indiana?
Indiana data science manager roles are posted by Cook, Goshen College, and Indiana University and others right now, based on current listings on Migrate Mate as of November 2026. Indiana's large healthcare systems, financial services firms, and enterprise technology companies are among the most consistent sources of data science manager openings in the state.
Which Indiana cities have the most data science manager jobs?
Indianapolis, Indiana, and Goshen have the most data science manager openings in Indiana. Indianapolis leads because it is home to major healthcare networks, insurance companies, and technology employers that run large analytics teams, while Fort Wayne and Bloomington generate openings through regional healthcare systems, manufacturing operations, and Indiana University's research and administrative functions.
How can I get hired as a data science manager in Indiana with little or no experience?
The most realistic path is moving from a senior individual contributor role, such as data scientist, data analyst, or machine learning engineer, into a lead or principal position before stepping into formal management. Indiana employers like Eli Lilly, Indiana University Health, and OneAmerica run rotational analytics programs and internal development tracks that promote high-performing contributors. Building a portfolio of end-to-end project leadership and pursuing a graduate degree or professional certification in data science or analytics significantly strengthens candidacy.
Where can I find and apply to data science manager jobs in Indiana?
You can find and apply to data science manager jobs in Indiana on Migrate Mate, which lists current Indiana openings. Search the roles that fit your background and apply directly to the ones that match your experience and target location.
See All 6 Data Science Manager Jobs in Indiana
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