Senior Manager, Data Platform Engineering

Company Overview

Nova Biomedical: One Global Brand. One Vision. Together under one name. Advanced Instruments and Nova Biomedical are now united under one brand, Nova Biomedical, marking a major milestone in our journey to deliver greater value to our customers. By combining our strengths, we are accelerating innovation, supporting critical workflows, and delivering world-class service across the biopharmaceutical and clinical markets.

Driven by innovation and guided by our core values — Customer Centricity, Ingenuity, Ownership & Accountability, Collaboration, and Integrity — Nova creates solutions that make a global impact. At Nova, candidates will find opportunities to grow, contribute, and help build a culture focused on transparency, sustainability, effective communication, and employee engagement.

Job Summary

The Sr Manager, Data Platform Engineering will lead Nova's data analytics and data science capability. The successful candidate will have a strong data science background first, while also showing the ability to grow and oversee data analytics and reporting. This role is fundamentally responsible for two areas: helping build trusted enterprise insights (data analytics) while also advancing predictive and prescriptive methods and core machine learning models/algorithms (data science) to enable the business, improve customer experience, generate product insights, and expand product performance via models deployed within or external to the product.

Why This Role Matters

• Lead a high-impact data science function at the center of Nova's digital, data, and AI transformation.

• Create trusted analytics and modeling capabilities that can influence decisions across the enterprise.

• Build the bridge between immediate insight needs and a modern, scalable data foundation.

• Create the foundation for data science capabilities that will directly support product innovation.

Responsibilities

• Enterprise role and technical expert leading data science and analytics across priority business domains (workforce, customer, and product)

• Build and manage a roadmap for trusted reporting, self-service analytics, data science, and advanced analytics use cases.

• Manage internal employees and external consultants, including data scientists, analysts, and report developers.

• Establish standards for analytical methods, dashboard design, metric definitions, model validation, documentation, and insight delivery.

• Partner with business leaders to identify high-value opportunities and convert ambiguous questions into prioritized analytical work.

• Oversee forecasting, classification, optimization, anomaly detection, statistical analysis, experimentation, and model validation efforts.

• Ensure analytics outputs align with governance, data quality, regulatory, and source-of-truth expectations.

Qualifications

• Master’s degree in data science, statistics, analytics, engineering, computer science, business analytics, or a related field; PhD preferred.

• Significant (10+ yrs) experience in analytics, BI, data science, applied machine learning, and enterprise insight delivery.

• Experience managing technical analytics teams, consultants, or cross-functional analytical programs.

• Strong knowledge of statistical analysis, data visualization, forecasting, model validation, business performance measurement, and dashboarding.

• Familiarity with modern data platforms, governed semantic/data models, and enterprise reporting environments.

• Strong executive communication, stakeholder management, and prioritization skills.

Preferred Experience

• Experience in medical device, diagnostics, life sciences, regulated manufacturing, or healthcare environments.

• Experience harmonizing analytics across ERP, CRM, data lake/lakehouse, IoT device data, complaints and field data.

• Experience building analytics operating models, metric registries, or self-service analytics programs.

What Success Looks Like

• Analytics and data science work is prioritized around measurable business impact.

• Reporting trust improves through clearer definitions, governance, documentation, and adoption.

• Data science use cases generate practical recommendations, measurable value, and reusable methods.

Benefits and Growth

Nova offers competitive benefits designed to support employee health, financial security, work-life balance, and professional growth. Benefits vary by country and employment type; full-time employees can generally expect comprehensive health coverage, retirement savings options, paid time off, wellness initiatives, and resources for development.