Data Science Insurance Jobs in Indiana (NOW HIRING)

Job Overview:

Pay Range $64hr - $67hr

Requirement/Must Have:

• 5-7+ years of experience building and deploying machine learning algorithms, complex data models, or automated software tools to support enterprise-level decision-making.
• Strong hands-on engineering proficiency with enterprise data science environments (such as Dataiku or ML Studio).
• Advanced understanding of NLP, LLMs, and prompt engineering architectures.
• Strong proficiency in core programming for data modeling (Python, SQL) and developer workflows (Git, Jira, Confluence, and script automation environments).
• Solid structural knowledge of cloud data warehousing (Snowflake), pipeline concepts (AWS), and business intelligence delivery tools (ThoughtSpot, Tableau).
• Experience working within a highly regulated manufacturing environment (such as Pharma, Diagnostics, or Medical Devices).
• Sound understanding of GxP compliance, US FDA 21 CFR Part 820 Quality Management System Regulations, and ISO 13485/9001 standards.
• Proven capability acting as a principal technical leader, driving global cross-functional projects, and aligning stakeholder expectations with a team-first, agile mindset.

Responsibilities:

• Design, scale, and deploy robust machine learning and NLP pipelines utilizing approved enterprise data platforms, primarily focusing on Dataiku and Azure ML Studio layers.
• Evaluate and deploy advanced AI solutions. Utilize the Claude Agent SDK or comparable approved SDKs as targeted implementation options for complex use cases that genuinely require custom, automated agents to navigate cross-system data silos.
• Architect and Experienced our global AI Use-Case Backlog. Guide the deployment of Natural Language Processing (NLP) and Large Language Models (LLMs) to automate initial sorting, risk-grading, and real-time categorization of complex quality data.
• Oversee the conceptual data modeling and integration pipelines feeding into core analytics repositories (such as Snowflake and AWS). Partner with builders to translate complex datasets into high-performing enterprise business intelligence views.
• Assume formal Product Owner and architectural design oversight for core Quality Insight platforms, dashboards, and automation frameworks.
• Establish and champion clean repository management, version control, and collaborative code review practices via Git. Drive standardized automation workflows utilizing Jira and Confluence to optimize the subchapter's intake pipeline and eliminate communication latency.
• Ensure all deployed AI models, automated scripts, and data pipelines adhere to computerized system validation protocols under GxP, US FDA (21 CFR Part 820), and ISO 13485 standards. Guide the team in authoring, reviewing, and executing technical validation documentation for data integrity.
• Partner directly with Quality Site Heads, Business Leaders, and global cross-functional squads to break down organizational data silos and resolve systemic reporting barriers across site networks.
• Establish, champion, and mentor an Operations Quality Community of Practice for Quality AI & Data Insights. Elevate organizational digital fluency by coaching other team members on best practices.
• Maintain a 95%+ alignment between automated AI/analytical insights and manual audit findings, fully meeting software validation protocols.
• Drastically reduce the cycle time required to compile and generate monthly and quarterly quality reports across the global network via automated data assembly.
• Secure high active usage metrics for all owned enterprise data products, capturing measurable efficiency savings.

Skills:

• Strong verbal and written communication skills.
• Excellent communication and presentation skills.
• Ability to communicate effectively with stakeholders.

Education and Experience:

• Bachelor's, Master's, or Ph.D. degree in Data Science, Informatics, Data Analytics, Computer Science, or a related technical field.
• Hands-on experience or deep conceptual understanding of custom agent architectures utilizing tools like the Claude Agent SDK or comparable enterprise-approved development kits.