Lead the design, development, and deployment of advanced statistical, machine learning, and AI solutions—including LLM-powered applications—to solve complex business, workforce, and organizational challenges.
Translate ambiguous business and HR questions into well-defined analytical approaches, scalable data products, and decision-support tools.
Design and oversee end-to-end data science workflows, including data extraction (e.g., enterprise data warehouses), validation, modeling, deployment, and performance monitoring.
Integrate data from multiple internal and external sources to create modeling-ready datasets, reusable data assets, semantic layers, and metadata frameworks that enable scalable and self-service analytics.
Develop and productionize predictive and prescriptive models to explain outcomes, forecast behavior, and identify risks and opportunities.
Build and deploy advanced AI solutions using modern frameworks (e.g., LLMs, embeddings, RAG architectures), and lead experimentation and rapid prototyping to evaluate emerging capabilities.
Embed analytics and AI solutions into business processes through automation, system integration, and near real-time data capabilities.
Partner with HR Business Partners, talent leaders, executives, data engineering, and IT teams to deliver actionable insights and ensure alignment with architectural, security, and data quality standards.
Provide technical leadership across data science initiatives, ensuring consistency with best practices, methodologies, and quality standards.
Communicate complex analytical insights and AI concepts clearly to non-technical stakeholders, influencing strategic and operational decision-making.
Mentor and coach junior team members, elevating team capabilities in AI, machine learning, and analytics best practices.
Ensure adherence to responsible AI principles, including data privacy, bias mitigation, security, and ethical use of employee data.
Stay current on emerging AI and analytics trends, proactively identifying opportunities to incorporate new technologies into enterprise use cases.
Requirements
Bachelor’s degree in a quantitative field required; advanced degree preferred.
Minimum of 6 years of relevant analytical or data science experience.
Demonstrated depth in multiple core data science disciplines (e.g., ML/statistics, data engineering, automation).
Advanced SQL and data modeling experience across complex data environments.
Proven ability to independently manage multiple initiatives and provide direction to others.
Strong written and verbal communication skills.
Experience working in regulated or complex operational environments preferred.
Demonstrated leadership capability and a track record of delivering high-impact analytical solutions.