Senior Manager, Data Platform Engineering

Nova Biomedical Corporation•Waltham, MA

1d•Onsite

About The Position

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. 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.

Requirements

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.

Nice To Haves

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.

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.