Lead the development of data-driven solutions for a next-generation insulin therapy platform by applying machine learning and statistical modeling techniques. This role focuses on transforming raw device data into meaningful insights that directly improve patient outcomes. You will design and manage data pipelines, develop preprocessing workflows, and build scalable algorithms tailored to insulin pump optimization.
Key Responsibilities
- Collaborate with IT and interdisciplinary teams to define and integrate data sources, ensuring reliable ingestion and storage architectures.
- Create and maintain scripts for data cleaning, transformation, and analysis using industry-standard tools.
- Investigate patterns in clinical and device data through exploratory analysis and custom-built programs.
- Design, validate, and deploy machine learning models that support therapy personalization.
- Communicate technical findings to leadership and non-technical stakeholders in alignment with strategic goals.
- Provide technical guidance and mentorship to junior team members.
- Contribute to ad hoc projects as needed to support product and research objectives.
Qualifications
Candidates must have at least five years of hands-on experience in machine learning, artificial intelligence, or statistical inference. A Master’s or doctoral degree in Computer Science, Electrical and Computer Engineering, or a closely related discipline is preferred. Prior experience in healthcare or medical devices is a strong advantage.
Proficiency in analytical tools such as Python, R, or MATLAB is required. Experience with SQL and relational databases—including Oracle, Teradata, or Microsoft SQL Server—is essential. Familiarity with programming languages like C/C++, C#, or Java is beneficial. Knowledge of Business Intelligence platforms such as Tableau, Spotfire, or Cognos is considered a plus. A solid understanding of software engineering principles and the ability to operate with minimal supervision while maintaining clear communication with stakeholders is expected.
Work Environment
This is a hybrid position based in Guadalajara, requiring on-site presence at least three days per week. The ideal candidate thrives in a performance-driven, collaborative environment committed to exceeding customer expectations through innovation and shared values.
