1

Director Predictive Analytics Jobs in Ohio (NOW HIRING)

Job Title Director, Business Intelligence Team Department Solution Delivery Worker Type Regular Pay ... Experience applying predictive analytics, machine learning, or AI capabilities to business or ...

Supply Chain Director

Youngstown, OH · On-site

$100 - $130/hr

The Director of Supply Chain plays a critical role in leading the strategic direction and building ... Leverage AI technologies where applicable to enhance predictive analytics capabilities.

Supply Chain Director

Youngstown, OH · On-site

$171K - $193K/yr

The Director of Supply Chain plays a critical role in leading the strategic direction and building ... Leverage AI technologies where applicable to enhance predictive analytics capabilities.

Showing results 21-40

Director Predictive Analytics information

What are the key skills and qualifications needed to thrive as a director of predictive analytics?

To thrive as a Director of Predictive Analytics, you need advanced expertise in statistics, machine learning, and data analysis, typically supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with tools such as Python, R, SQL, cloud-based analytics platforms, and relevant certifications in data science or analytics software are highly valued. Exceptional leadership, strategic thinking, and communication skills help you translate complex data insights into actionable business strategies and manage cross-functional teams effectively. These competencies are crucial for driving data-informed decision-making and maximizing the value of predictive analytics within an organization.

What jobs use predictive analytics?

Predictive analytics is used in a variety of roles such as data analysts, data scientists, business analysts, and marketing analysts. These jobs involve analyzing data to forecast trends, improve decision-making, and optimize processes using tools like statistical software and machine learning algorithms.

What is the difference between Director Predictive Analytics vs Data Scientist?

AspectDirector Predictive AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often requires leadership experienceBachelor's or Master's in Data Science, Statistics, Computer Science, or related field
Work EnvironmentLeads teams, manages projects, collaborates with executivesAnalyzes data, develops models, reports findings
Employer & Industry UsageUsed in corporate, finance, healthcare, and tech sectors for strategic decision-makingCommon across tech, finance, marketing, and research sectors for data analysis

The main difference is that the Director Predictive Analytics oversees teams and strategic projects, focusing on leadership and high-level decision-making, while Data Scientists primarily analyze data and build models to derive insights. Both roles require strong analytical skills and knowledge of data tools, but the director position emphasizes management and strategic alignment.

What are the typical collaboration points for a director of predictive analytics within an organization?

A Director of Predictive Analytics regularly collaborates with cross-functional teams, including data engineers, data scientists, business stakeholders, and IT departments. They are responsible for translating business needs into analytical solutions, ensuring data quality, and integrating predictive models into operational systems. Strong communication is essential, as the director must bridge technical teams and business leaders to drive data-driven decision-making throughout the organization.

What does a director of predictive analytics do?

A Director of Predictive Analytics leads teams that use data, statistical algorithms, and machine learning techniques to forecast future outcomes and trends for a business. They are responsible for developing and implementing predictive models that drive strategic decisions in areas such as marketing, operations, and risk management. This role often involves collaborating with executives, data scientists, and IT professionals to ensure analytics solutions align with organizational goals. Additionally, the Director oversees data quality, project management, and the adoption of analytical best practices across the company.

What are the most commonly searched types of Predictive Analytics jobs in Ohio?

The most popular types of Predictive Analytics jobs in Ohio are:

What cities in Ohio are hiring for Director Predictive Analytics jobs?

Cities in Ohio with the most Director Predictive Analytics job openings:

Infographic showing various Director Predictive Analytics job openings in Ohio as of August 2026, with employment types broken down into 100% Full Time. Highlights an 94% In-person, and 6% Remote job distribution.

AVP, Business Intelligence & Analytics Engineering

CareSource

Dayton, OH • On-site, Remote

Full-time

Posted 9 days ago


CareSource rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

202nd of 306 rated insurance


Job description

Job Summary:
The AVP, Business Intelligence & Analytics Engineering is a senior technology leader responsible for advancing CareSource's data analytics, data science, and artificial intelligence capabilities across the enterprise. This role partners directly with clinical, financial, and operational business units to translate complex data assets into actionable intelligence - driving measurable improvements in member outcomes, Stars & HEDIS performance, risk stratification, and operational efficiency. The AVP leads three integrated practice areas: Business Intelligence & Reporting, Data Science & Predictive Analytics, and AI/ML Engineering.
Essential Functions:
  • Own the enterprise Business Intelligence, Analytics, and Data Products strategy, governance, and multi-year roadmap across the health plan, including claims, clinical, Stars/HEDIS, HCC risk, and Member 360 domains.
  • Partner with Finance, Clinical Operations, Stars Coordination, Network Management, and other business leaders to define enterprise KPIs, performance metrics, and self-service analytics capabilities that support strategic decision-making.
  • Establish enterprise data product standards, governance practices, and delivery frameworks that ensure scalable, trusted, and auditable analytics capabilities across the organization.
  • Evaluate and manage analytics and BI technologies, including vendor platforms and Databricks-native capabilities, and lead build-versus-buy recommendations for executive leadership.
  • Ensure all analytics products and reporting outputs comply with HIPAA, CMS, state regulatory, and enterprise governance requirements.
  • Lead the enterprise data science function, driving predictive and prescriptive analytics solutions that improve clinical outcomes, operational performance, member experience, and financial results.
  • Oversee the development, deployment, and ongoing optimization of advanced analytic models supporting risk adjustment, quality improvement, population health management, utilization management, care gap closure, fraud detection, and other strategic business priorities.
  • Establish and operationalize an enterprise model lifecycle management framework, including feature management, experiment tracking, validation standards, model monitoring, and production deployment practices.
  • Partner with Care Management, Quality, Provider Relations, Clinical Operations, and other business stakeholders to translate analytic insights into measurable operational and clinical improvements.
  • Build, lead, and develop a high-performing organization of BI developers, data engineers, data scientists, ML engineers, statisticians, and analytics professionals, including workforce planning, succession management, career development, technical skill advancement, and organizational capability building.
  • Own the strategy, architecture, governance, and evolution of the enterprise AI/ML platform, ensuring scalable, secure, and compliant deployment of advanced analytics and artificial intelligence capabilities.
  • Lead the identification, prioritization, and execution of enterprise AI and generative AI use cases that improve business performance, enhance member and provider experiences, and increase organizational productivity.
  • Establish and oversee responsible AI governance, including model risk management, fairness and explainability standards, bias monitoring, human oversight controls, AI ethics review processes, and audit readiness for regulatory and compliance reviews.
  • Drive enterprise adoption of generative AI capabilities, including large language model (LLM) and retrieval-augmented generation (RAG) solutions, model evaluation frameworks, cost optimization strategies, and scalable deployment patterns.
  • Collaborate with Information Security, Compliance, Legal, Privacy, and Technology leadership to ensure AI systems meet regulatory, security, auditability, and vendor risk management requirements.
  • Develop reusable AI solution frameworks, accelerators, governance standards, and technical enablement resources that scale AI adoption across the enterprise.
  • Serve as a key member of the Enterprise Data Services leadership team, contributing to enterprise data strategy, AI strategy, talent strategy, and the multi-year technology roadmap.
  • Serve as the executive sponsor and primary advisor for enterprise analytics and AI initiatives, communicating strategy, performance, risks, opportunities, and business value to executive and Board-level stakeholders.
  • Own financial planning and budget accountability for the analytics, data science, and AI engineering portfolio, including workforce investments, technology platforms, infrastructure, and strategic vendor partnerships.
  • Foster a culture of innovation, continuous learning, experimentation, and responsible data- and AI-driven decision-making across the enterprise.
  • Perform any other job related duties as requested.

Education and Experience:
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Biomedical Informatics, or a related quantitative field is required
  • Master's degree or PhD in Data Science, Health Informatics, Applied Statistics, or equivalent preferred
  • Equivalent years of relevant work experience may be accepted in lieu of required education
  • Ten (10) years of progressive experience in data analytics, data science, or AI/ML engineering required
  • Four (4) years in a senior leadership role managing technical teams is required
  • Demonstrated experience in a managed care, health plan, or health insurance environment preferred
  • Proven track record of delivering production AI/ML solutions in regulated, privacy-sensitive environments preferred
  • Prior experience with Databricks (Unity Catalog, MLflow, Genie, Delta Live Tables) or equivalent modern lakehouse platforms strongly preferred
  • Experience in vendor evaluation, contract negotiation, and technology partnership management preferred
  • Experience with data governance frameworks including data cataloging, lineage, quality monitoring, and access control in a HIPAA-regulated context preferred
Competencies, Knowledge and Skills:
  • Advanced proficiency in Python, SQL, and statistical programming languages (e.g., R, SAS), with experience leveraging Spark/PySpark and modern machine learning frameworks to develop and deploy scalable analytics and AI solutions
  • Deep familiarity with claims, clinical, HEDIS/Stars, HCC, and member data models strongly preferred
  • Deep understanding of AI/ML and MLOps practices, including model lifecycle management, model monitoring, CI/CD pipelines, experiment tracking, generative AI technologies, LLMs, prompt engineering, RAG architectures, and vector databases
  • Strong strategic and business acumen, with the ability to align analytics, data science, and AI investments to organizational priorities, measurable outcomes, and mission impact
  • Exceptional executive communication and influencing skills, including the ability to translate complex technical concepts into clear business value for executive leadership, clinical stakeholders, regulators, and non-technical audiences
  • Proven leadership, talent development, and organizational management capabilities, with the ability to build, motivate, and lead high-performing teams in a collaborative and rapidly evolving environment
  • Demonstrated ability to establish trusted partnerships and effectively collaborate across clinical, operational, technology, compliance, finance, and vendor organizations to achieve enterprise objectives
  • Strong knowledge of healthcare and managed care data ecosystems, including HL7/FHIR standards, ICD-10/CPT coding, NCQA HEDIS specifications, CMS risk adjustment methodologies, and applicable regulatory requirements
  • Highly self-directed with the ability to manage multiple complex priorities, drive execution through ambiguity, and effectively leverage vendor, outsourcing, and staff augmentation strategies to support organizational goals
Licensure and Certification:
  • None
Working Conditions:
  • General office environment; may be required to sit or stand for extended periods of time
  • Ability to travel as required by the needs of the business.

Compensation range $150,000-$300,000. CareSource takes into consideration a combination of a candidate's education, training, and experience as well as the position's scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee's total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
Salary
Organization Level Competencies
  • Fostering a Collaborative Workplace Culture
  • Cultivate Partnerships
  • Develop Self and Others
  • Drive Execution
  • Energize and Inspire the Organization
  • Influence Others
  • Pursue Personal Excellence
  • Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
#LI-SW2
Brand=CareSource

What CareSource employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom