Clinical AI/Data Science Eng I

MiniMed•Los Angeles, CA

1d•$71,000 - $135,000

About The Position

MiniMed is seeking a Clinical Data Engineer to join its Bioinformatics team and develop scalable data solutions for clinical research, medical device studies, and real-world data initiatives. The role builds and optimizes data pipelines, integrates data from multiple sources, and transforms raw information into high-quality datasets for analytics, evidence generation, and decision-making. The engineer collaborates with Clinical Research, Biostatistics, R&D, and Software Engineering to support data quality, consistency, and usability across a diverse data ecosystem. The role involves developing clinical and medical-device data workflows, implementing ETL/ELT solutions, preparing analysis-ready datasets, and supporting data management and software testing activities. It also applies software engineering practices to produce reliable, maintainable code and may involve developing algorithms, programming and debugging solutions, and documenting installation and maintenance procedures. The position is an individual-contributor role in the technical specialist career stream, working independently with general supervision on moderately complex projects and potentially guiding entry-level colleagues. This is an office role whose physical demands include being independently mobile, interacting with a computer, and communicating with peers and co-workers. Reasonable accommodations may be made for individuals with disabilities. MiniMed offers competitive compensation and a flexible benefits package. The position is eligible for a short-term incentive. U.S. salary ranges are $71,000–$121,000, or $79,000–$135,000 in California, Seattle, Washington, D.C., Boston, and New York City; actual compensation varies based on factors such as experience, education, skills, market conditions, and location.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Biomedical Engineering, Statistics, or a related field, with 1–3 years of relevant experience; alternatively, 0–2 years of relevant experience with a master’s degree.
Advanced SQL proficiency, including complex joins, window functions, CTEs, and query optimization.
Hands-on experience with a data warehousing platform such as Snowflake, Databricks, BigQuery, Redshift, or Azure Synapse.
Proficiency in Python, including pandas, NumPy, and data visualization libraries such as matplotlib, seaborn, or plotly.
Experience with Power BI.
Practical knowledge and demonstrated competence in the job area, typically gained through advanced education combined with experience.

Nice To Haves

Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
Hands-on experience deriving insights and supporting decisions from large, complex datasets; stated experience level is 1–3 years, or 0–2 years with a master’s degree.
Working knowledge of foundational statistics, such as hypothesis testing, distributions, regression, sampling methods, multivariate analysis, survival analysis, or statistical process control.
Ability to translate technical findings into clear, actionable insights for cross-functional audiences.
Familiarity with ETL/ELT workflows and pipeline tooling.
Experience or genuine interest in medical technology, clinical studies, or healthcare data.
Interest in turning complex data into compelling narratives that drive action.
Experience with AI-assisted coding environments such as Amazon SageMaker Unified Studio, GitHub Copilot, or similar.
Experience with Power BI, Tableau, or similar dashboard and reporting platforms.
Experience with SQL, Databricks, AWS, and AWS Redshift.

Responsibilities

Design, develop, evaluate, and maintain pipelines, programs, and workflows for processing, validating, and analyzing clinical and medical-device data.
Build and support automated ETL/ELT solutions using Databricks, SQL, AWS services, and optionally PySpark to ingest and transform structured and semi-structured data, including JSON and CSV.
Collect, clean, transform, and standardize raw clinical and device data into high-quality, analysis-ready datasets.
Work with Biostatistics and study teams to understand analytical requirements and deliver finalized datasets for statistical software and downstream use.
Coordinate with Medical Device and Software Engineering teams on data schemas, firmware updates, data payload specifications, and system integration requirements.
Identify data inconsistencies, perform root cause analysis, and implement solutions to improve data quality, accuracy, and completeness.
Support clinical data management through data mining, validation, reconciliation, and issue resolution across multiple sources.
Contribute to data management plans supporting study, project, and protocol timelines.
Provide technical support for software user acceptance testing and review training materials, instructions, and documentation for clinical data systems.
Serve as a liaison among Clinical Research, R&D, Biostatistics, and other stakeholders to communicate timelines, requirements, and deliverables.
Apply version control, CI/CD, code review, and other software engineering practices to create reliable, maintainable solutions.
Manage multiple projects independently in a deadline-driven environment while maintaining quality and accountability.
Develop and evaluate algorithms to characterize product and system performance, quality, data management, and accuracy.
Translate algorithms and technical specifications into code using current programming languages and technologies.
Program, test, debug, and implement efficiencies; document installation and maintenance procedures.
Work with large-scale computing frameworks, data analysis systems, and modeling environments.
May provide guidance and assistance to entry-level professionals or employees in the Support Career Stream.

Benefits

Competitive salary and flexible benefits package.
Health insurance.
Dental insurance.
Vision insurance.
Health Savings Account access.
Healthcare Flexible Spending Account access.
Life insurance.
Long-term disability leave.
Dependent daycare spending account.
Incentive plans, including eligibility for the Short Term Incentive (STI).
401(k) plan with company match.
Short-term disability coverage.
Paid time off and holidays.
Employee Stock Purchase Plan participation.
Employee Assistance Program access.
Eligible employees may have access to a Non-qualified Retirement Plan Supplement and Capital Accumulation Plan, subject to IRS minimum earnings requirements.