Job description
Description
About OGC
OGC is a boutique research and consulting firm specializing in data-driven strategy, AI-powered quantitative analytics, customer experience (CX) analytics, and innovation testing. We partner with Fortune 500 organizations across Financial Services, Specialty Retail, Telecommunications, Hospitality, Software, and Healthcare to uncover insights, improve decision-making, and drive measurable business impact. Our approach is hands-on and collaborative: deep discovery, advanced analytics using state-of-the-art tools, cross-functional problem solving, and executive-ready storytelling that turns insight into action.
Role Overview
We are seeking a Data Science & AI Project Lead to join our team and operate as an embedded expert within the Data Science and Innovation organization of a large, nationally scaled healthcare enterprise. This is a hybrid delivery role: part orchestration, part analytics leadership. You will lead the execution of a high-visibility AI and synthetic data strategy, while also remaining close enough to the work to credibly engage on modeling approaches, data pipelines, and analytical methodologies. You will manage numerous stakeholders including senior data scientists, product leaders, and executives, ensuring complex data science initiatives move from experimentation to production with clarity, governance, and momentum. This role is ideal for someone who is technically fluent in AI/ML and synthetic data, comfortable in regulated environments, and excels at influence, structure, and executive communication.
Key Responsibilities
Lead end-to-end delivery of data science and AI initiatives, from scoping through production
Facilitate requirements gathering and project scoping for high-priority AI, analytics, and synthetic data initiatives
Own delivery cadence, prioritization, dependencies, and risk management across a multi-year AI roadmap
Apply Agile, Scrum, or hybrid methodologies to maintain momentum and transparency
Define and document technical specifications for synthetic data generation, modeling, and deployment
Support execution of quantitative research and data science projects, including:
Data preparation and transformation
Modeling (classification, regression, forecasting, etc.)
Insight generation and reporting
Oversee data pipeline flows and manage incoming stakeholder requests (data cuts, model refinements, ad-hoc analysis)
Conduct functional QA to ensure analytical and synthetic data outputs meet accuracy, usability, and business requirements
Serve as the primary liaison between technical teams and non-technical business, clinical, and operational stakeholders
Translate complex data science progress into clear, credible executive narratives
Build and deliver insights-based presentations and status updates to senior stakeholders
Facilitate workshops and enablement sessions to drive adoption of AI tools and analytical outputs
Support development of reusable data science products and internal accelerators
Research and evaluate new data sources, tools, and methodologies
Provide expert guidance on analytical techniques to analysts, data scientists, and sales leaders
Help institutionalize best practices for AI governance, synthetic data use, and analytics at scale
Requirements
BA/BS in Computer Science, Data Science, Business, or a related field
MA/MS in Data Science, Computer Science, Business Analytics, or similar — an advantage
4+ years experience in data science, analytics, or AI-focused roles
3+ years experience leading or coordinating data science or AI projects
Experience working with healthcare, life sciences, or regulated data environments — strong advantage
Consulting or client-facing experience with senior stakeholders
Machine Learning & statistical modeling
Data pipelines and analytics workflows
Python (Pandas, NumPy, Scikit-learn, XGBoost, PySpark, etc.)
SQL
Statistics and quantitative research methods
Data visualization tools (Tableau, Power BI — advantage)
Exceptional ability to translate technical detail into business value
Strong analytical thinking and structured problem-solving
Comfortable operating independently as an embedded resource
Excellent written and spoken English (fluent and idiomatic)
