Principal Analytics Platform Engineer

Overview

We are constantly looking to add to our core talent. If you are seeking a career that is challenging and rewarding, a work environment that is diverse and dynamic, Haemonetics is your employer of choice.

Haemonetics R&D is seeking a Principal Analytics Platform Engineer to own, extend and operationalize an existing analytics platform that enables cross-disciplinary teams to derive insights from complex in-house and customer thromboelastography data. This role sits at the intersection of analytics, data science, and software engineering, focusing on advancing analytical workflows, scaling data access, and translating instrument-level data into reliable, decision-ready insights for R&D, clinical research, and product development.

You will be responsible for maintaining, extending and operationalizing our analytics infrastructure—ensuring data pipelines, computational workflows, and services are stable, scalable, secure, and compliant—while also owning key components of our internal FastAPI-based application that exposes analytical and operational capabilities to end users across R&D, Quality, Service, Manufacturing, and other cross-functional teams. Over time, this platform is expected to integrate more directly with enterprise and product-facing systems.

A core expectation of this role is the ability to both perform and lead deep analytical work—spanning data mining, exploratory and confirmatory analysis, feature extraction, and predictive modeling—and to translate those results into clear, actionable outputs for a broad audience, including stakeholders who do not work directly in code- or notebook-based environments. This role is expected to quickly get up to speed on TEG data, actively mine existing and newly generated datasets, build analytical tools and frameworks that scale insight generation, and serve as an integral thought partner to Systems, R&D, Quality, and Product teams by bringing forward new analytical ideas, hypotheses, and early-signal detection approaches.

Job Details

• Maintain and improve in-house data warehousing and analytics platform solutions
• Assist with R&D experiment planning and analysis by investigating and structuring raw instrument data
• Design and maintain data pipelines and computational workflows routinely that support reproducible analysis
• Collaborate with R&D, Marketing, and Field Clinical Services to investigate product incident reports within appropriate regulatory frameworks
• Develop and maintain FastAPI-based services that expose analytical and operational capabilities to internal users
• Ensure analytical outputs are delivered in standard, portable formats (e.g., files compatible with JMP and other common statistical analysis tools), enabling downstream use without requiring knowledge of Jupyter notebooks or programming environments
• Prototype and evaluate emerging AI/ML solutions that advance organizational goals
• Define and implement consistent data and study labeling standards (e.g., data custody, metadata conventions, and standardized study indexing) to improve traceability, reuse, and cross-study analysis
• Design and develop tools and interfaces that enable secure integration with enterprise systems (e.g., Oracle, Salesforce, and other internal platforms), expanding analytics reach across the organization

• Ability to understand, maintain, and iterate on legacy codebases (Python, SQL,
  
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• Experience with data modeling and OLAP data solutions
• Experience with Python web frameworks (FastAPI)
• Experience with Python notebook environments (Jupyter, marimo), with an understanding of their limitations for broad data consumption
• Strong documentation practices, enabling transparency, traceability, reproducibility, and independent review
• Ability to communicate complex technical and analytical concepts clearly to a broad, cross-functional audience
• Ability to troubleshoot and support Linux and Windows server environments
• Working knowledge of statistics and specialized statistical software (e.g., JMP, TABLEAU, Minitab)
• Graduate degree in life sciences or computer sciences preferred

Pay Transparency:

The base pay actually offered to the successful candidate will…