SGS is the world's leading Testing, Inspection and Certification company. We operate a network of over 2,700 laboratories and business facilities across 119 countries, supported by a team of 99,250 dedicated professionals. With over 145 years of service excellence, we combine the precision and accuracy that define Swiss companies to help organizations achieve the highest standards of quality, safety and compliance.
Our brand promise, when you need to be sure, underscores our commitment to reliability, integrity and trust — enabling businesses to thrive with confidence. We proudly deliver our expert services through the SGS name and trusted specialized brands, including Brightsight, Bluesign, Maine Pointe and Nutrasource.
SGS is publicly traded on the SIX Swiss Exchange under the ticker symbol SGSN (ISIN CH0002497458, Reuters SGSN.S, Bloomberg SGSN:SW).
The Sr. Health & Benefits Data Analyst turns complex health and benefits data into clear, actionable insights. This role uses advanced data analytics, multivariate analyses, dashboards, benchmarking, and AI-driven analysis to show how effective programs deliver measurable results, helping position the organization as a leader in benefit analytics. We are looking to hire at least 2 positions.
Job functions:
Data Analysis & Insights
- Analyze data related to benefits, including medical claims, pharmacy claims, wellbeing programs, ergonomics, workers’ compensation, disability, flexible work schedule, paid time off, and other benefits. Identify trends, correlations, and leading indicators linking health and wellbeing programs, initiatives, and design to reductions in claims, accidents, and lost-time incidents.
- Support descriptive, diagnostic, predictive, and prescriptive analyses across benefits programs (e.g., mental health, fertility, medical, ergonomics, occupational health and safety (OHS)).
- Enable ongoing evaluation of benefit suppliers and point solutions, including program effectiveness, utilization, outcomes, and cost impact.
- Build predictive models to forecast risk exposure, claim frequency/severity, and potential impact of preventive interventions.
- Design and deploy AI-driven models (machine learning, NLP, anomaly detection) to uncover hidden patterns in health, safety, and benefits data.
- Translate business and research questions into analytic requirements and ensure outputs are accurate, interpretable, and decision‑ready.
- Review