Overview In this role you drive analytics strategy and data-driven decision making across Insulet, enabling smarter business choices and innovation in life-changing technologies like Omnipod. You lead the Analytics COE, mentoring data scientists and shaping tools and processes to transform data into actionable insights for products, patients, and operations. You work at the intersection of data, healthcare, and leadership to scale analytics and ML workflows in cloud environments. You will engage cross-functionally to deliver high-impact data products that support R&D, clinical, quality, and manufacturing while advancing the company's mission.
Compensation / Benefits- Medical, dental, and vision insurance
- 401(k) with company match
- Paid time off
- Wellness programs
Responsibilities- Interface with IT, executives, and cross-functional leaders to identify high-value data science opportunities and coordinate execution with Analytics COE scientists
- Manage a team of data scientists to deliver high-quality analytics work and foster talent development and retention
- Own the data products and insights delivery portfolio and guide cloud-based ML/analytics pipelines (Azure, AWS, GCP)
- Explore data patterns using existing tools and self-created programs to derive insights
- Perform statistical analysis, predictive modeling, and automated reporting as required
- Clearly communicate findings to a broad audience in the context of business objectives
- Maintain a yearly budget with periodic updates and reforecasting
- Perform other duties as required
Key requirements- Master's with 5+ years of experience or PhD with 3+ years in Data Science, Mathematics, Computer Science, Electrical and Computer Engineering, or related field
- At least 2 years of work experience in machine learning, AI, or statistical inferences
- Experience directly managing teams in fast-paced environments and in medical device or healthcare industries
- Effective leadership in fast-paced environments
- Influence and align teams on guiding principles
- Ability to manage conflicting priorities among stakeholders
- Python or R
- Cloud computing and big data technologies (Databricks/Spark on Azure or AWS)
- SQL and relational databases (Oracle, Teradata, Microsoft SQL Server)
