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Senior Manufacturing AI/Data Science Engineer

Northridge, California, United States of America

Live, first seen by us 28 days ago
Pay
Multiple pay amounts — pay source
At MiniMed, we put people first. A commitment to our employees lives at the core of our values: We recognize their contributions. They share in the success they help create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every stage of your career and life. Salary ranges for U.S (excl. PR) locations (USD):$112,000.00 - $190,000.00For roles located in California, Seattle WA, Washington DC, Boston MA, and New York City, the salary range is $112,000.00 - $190,000.00 USD. Actual compensation may vary based on factors including experience, education, certifications, skills, market conditions, internal equity, and geographic location. Compensation and benefits information pertain solely to candidates hired within the United States (local market compensation and benefits will apply for others)
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Candidates can be either of our Northridge CA office or our St.

MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer to join our Data Science team in a dedicated capacity supporting manufacturing, supply chain, operations, and new product introduction (NPI) functions.

  • You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world.

From the employer’s posting
Candidates can be either of our Northridge CA office or our St. Louis Park MN office. Must be onsite 3 days per week/2 day remote.
MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer to join our Data Science team in a dedicated capacity supporting manufacturing, supply chain, operations, and new product introduction (NPI) functions.
We anticipate the application window for this opening will close on - 9 Nov 2026 At MiniMed, you can begin a lifelong career of exploration and innovation, while helping make a difference in the lives of people living with diabetes around the globe. You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world. About the Role

What you’ll bring

All qualifications

Core experience

  • Bachelor’s degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, Chemical Engineering, Electrical Engineering, Quality Engineering, Operations Research, Data Science, Statistics, Computer Science, or a related technical or quantitative field.
  • Practical experience with relevant statistical and manufacturing methods, including root cause analysis, statistical process control, process capability analysis, hypothesis testing, regression, and design of experiments.
  • Proficiency using Python, R, SQL, Minitab, JMP, MATLAB, or similar analytical tools to investigate complex problems, develop analytical solutions, and communicate results.
  • Experience translating manufacturing problems into analytical approaches and converting analytical results into practical recommendations.
  • Ability to determine when traditional statistical methods, machine learning, AI, or other analytical techniques are appropriate for a given manufacturing problem.
  • Experience collaborating across manufacturing, engineering, quality, supply chain, IT, data engineering, and leadership functions in a cross-functional or matrixed environment.

Preferred experience

  • Master’s degree or PhD in an engineering, scientific, data science, statistics, computer science, or related quantitative discipline.
  • Experience working in a regulated manufacturing industry such as medical devices, pharmaceuticals, aerospace, automotive, or another highly controlled production environment.
  • Familiarity with applicable data integrity, validation, quality-system, or regulatory requirements, including FDA or GxP expectations.
  • Knowledge of Lean Manufacturing, Six Sigma, DMAIC, or related continuous-improvement methodologies; Green Belt or Black Belt certification is a plus.
Qualification wording
Bachelor’s degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, Chemical Engineering, Electrical Engineering, Quality Engineering, Operations Research, Data Science, Statistics, Computer Science, or a related technical or quantitative field.
Practical experience with relevant statistical and manufacturing methods, including root cause analysis, statistical process control, process capability analysis, hypothesis testing, regression, and design of experiments.
Proficiency using Python, R, SQL, Minitab, JMP, MATLAB, or similar analytical tools to investigate complex problems, develop analytical solutions, and communicate results.
Experience translating manufacturing problems into analytical approaches and converting analytical results into practical recommendations.
Ability to determine when traditional statistical methods, machine learning, AI, or other analytical techniques are appropriate for a given manufacturing problem.
Experience collaborating across manufacturing, engineering, quality, supply chain, IT, data engineering, and leadership functions in a cross-functional or matrixed environment.
Master’s degree or PhD in an engineering, scientific, data science, statistics, computer science, or related quantitative discipline.
Experience working in a regulated manufacturing industry such as medical devices, pharmaceuticals, aerospace, automotive, or another highly controlled production environment.
Familiarity with applicable data integrity, validation, quality-system, or regulatory requirements, including FDA or GxP expectations.
Knowledge of Lean Manufacturing, Six Sigma, DMAIC, or related continuous-improvement methodologies; Green Belt or Black Belt certification is a plus.
Education & alternatives
Required Qualifications - Bachelor’s degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, Chemical Engineering, Electrical Engineering, Quality Engineering, Operations Research, Data Science, Statistics, Computer Science, or a related technical or quantitative field. - Five or more years of relevant professional experience, including significant experience in manufacturing, manufacturing engineering, process engineering, quality engineering, industrial operations, operational excellence, or a closely related environment.
Preferred Qualifications - Master’s degree or PhD in an engineering, scientific, data science, statistics, computer science, or related quantitative discipline. - Experience working in a regulated manufacturing industry such as medical devices, pharmaceuticals, aerospace, automotive, or another highly controlled production environment.

About Minimed

Learn more about our business, and our mission here.

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Posting record

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Status in our records
Live
First seen by us
Oct 6, 202628 days ago
Recorded sightings
33
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 28

Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Minimed is hiring

7 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is picking up
  • Its jobs tend to stay up a long time
Hiring record

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  • MLflow
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Where the posting names them
- Working knowledge of manufacturing systems and data, including one or more of the following: manufacturing execution systems, ERP systems, equipment data, sensor data, process parameters, quality systems, electronic batch or device history records, and production master data. - Proficiency using Python, R, SQL, Minitab, JMP, MATLAB, or similar analytical tools to investigate complex problems, develop analytical solutions, and communicate results. - Experience translating manufacturing problems into analytical approaches and converting analytical results into practical recommendations.
- Experience with computer vision, time-series modeling, anomaly detection, predictive maintenance, natural language processing, or generative AI applications relevant to manufacturing and operations. - Experience with cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Azure, or AWS. - Experience with data visualization and business-intelligence tools such as Power BI or Tableau.
- Experience with data visualization and business-intelligence tools such as Power BI or Tableau. - Familiarity with production deployment and MLOps practices or platforms such as MLflow, Azure Machine Learning, or AWS SageMaker. - Experience working with IoT, equipment, historian, control-system, or high-frequency sensor data.
- Experience with cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Azure, or AWS. - Experience with data visualization and business-intelligence tools such as Power BI or Tableau. - Familiarity with production deployment and MLOps practices or platforms such as MLflow, Azure Machine Learning, or AWS SageMaker.

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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

We anticipate the application window for this opening will close on - 9 Nov 2026

At MiniMed, you can begin a lifelong career of exploration and innovation, while helping make a difference in the lives of people living with diabetes around the globe. You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world.

About the Role

Must have Manufacturing experience!!!

Candidates can be either of our Northridge CA office or our St. Louis Park MN office. Must be onsite 3 days per week/2 day remote.

MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer to join our Data Science team in a dedicated capacity supporting manufacturing, supply chain, operations, and new product introduction (NPI) functions.



This role is responsible for accelerating the evolution of our cloud data infrastructure for manufacturing data sources, solidifying trusted operational metrics, supporting root cause investigations with advanced analytics, and progressively delivering predictive and AI-driven solutions that improve how we design, build, and deliver our products. The ideal candidate is a technically strong data scientist with experience in supply-chain, manufacturing, or a related industry who thrives in complex, cross-functional environments.

Candidates may work from either our Northridge, CA or St. Louis Park, MN office and must be onsite three days per week, with two remote days.

MiniMed is seeking a Senior Manufacturing AI/Data Science Engineer who combines deep manufacturing knowledge with strong analytics and data science capabilities. This role will apply statistics, advanced analytics, machine learning, and emerging AI technologies to solve complex challenges across manufacturing, quality, supply chain, operations, and new product introduction.


The successful candidate will work closely with manufacturing and cross-functional partners to investigate process and quality issues, improve manufacturing data and operational metrics, and deliver analytical solutions that improve product quality, process performance, operational efficiency, and decision-making. The role will also help identify and implement practical AI opportunities based on clearly defined manufacturing needs, data readiness, regulatory considerations, and measurable business value.


The ideal candidate has significant experience working in a manufacturing environment and a proven history of applying analytics, statistics, data science, or AI to solve manufacturing and operational challenges. They understand how products, processes, equipment, materials, quality systems, and operational decisions interact and can translate manufacturing problems into effective, data-driven solutions.


Essential Duties and Responsibilities
  • Serve as a trusted manufacturing analytics partner to manufacturing engineering, operations, quality, supply chain, and NPI teams, developing a strong understanding of production processes, equipment, materials, data flows, and key performance drivers.
  • Lead and support data-driven investigations into yield loss, scrap, defects, equipment performance, downtime, process variation, throughput, capacity, cycle time, and other manufacturing and quality challenges.
  • Apply statistical and analytical methods to identify sources of variation, evaluate potential causes, quantify relationships, and accelerate the resolution of complex manufacturing problems.
  • Partner with data engineering, IT, and manufacturing systems teams to improve the availability, context, quality, reliability, and governance of manufacturing data.
  • Apply appropriate methods such as statistical process control, process capability analysis, design of experiments, regression, multivariate analysis, time-series analysis, predictive modeling, machine learning, computer vision, or generative AI based on the specific manufacturing problem.
  • Identify practical opportunities to apply AI and machine learning across manufacturing, quality, supply chain, operations, and NPI, balancing technical potential with data readiness, regulatory requirements, implementation feasibility, and expected business value.
  • Communicate analytical findings and recommendations clearly to manufacturing teams, technical specialists, cross-functional partners, and leadership, connecting complex results to operational actions and measurable outcomes.

Required Qualifications
  • Bachelor’s degree in Manufacturing Engineering, Industrial Engineering, Mechanical Engineering, Chemical Engineering, Electrical Engineering, Quality Engineering, Operations Research, Data Science, Statistics, Computer Science, or a related technical or quantitative field.
  • Five or more years of relevant professional experience, including significant experience in manufacturing, manufacturing engineering, process engineering, quality engineering, industrial operations, operational excellence, or a closely related environment.
  • Demonstrated history of applying statistics, analytics, data science, machine learning, or AI to solve manufacturing, quality, supply chain, or operational challenges.
  • Practical experience with relevant statistical and manufacturing methods, including root cause analysis, statistical process control, process capability analysis, hypothesis testing, regression, and design of experiments.
  • Working knowledge of manufacturing systems and data, including one or more of the following: manufacturing execution systems, ERP systems, equipment data, sensor data, process parameters, quality systems, electronic batch or device history records, and production master data.
  • Proficiency using Python, R, SQL, Minitab, JMP, MATLAB, or similar analytical tools to investigate complex problems, develop analytical solutions, and communicate results.
  • Experience translating manufacturing problems into analytical approaches and converting analytical results into practical recommendations.
  • Ability to determine when traditional statistical methods, machine learning, AI, or other analytical techniques are appropriate for a given manufacturing problem.
  • Experience collaborating across manufacturing, engineering, quality, supply chain, IT, data engineering, and leadership functions in a cross-functional or matrixed environment.
  • Proven ability to manage multiple priorities, work through ambiguous problem definitions, and deliver solutions that produce measurable operational or business value.

#BetterWorkdaysStartNow


Preferred Qualifications
  • Master’s degree or PhD in an engineering, scientific, data science, statistics, computer science, or related quantitative discipline.
  • Experience working in a regulated manufacturing industry such as medical devices, pharmaceuticals, aerospace, automotive, or another highly controlled production environment.
  • Familiarity with applicable data integrity, validation, quality-system, or regulatory requirements, including FDA or GxP expectations.
  • Knowledge of Lean Manufacturing, Six Sigma, DMAIC, or related continuous-improvement methodologies; Green Belt or Black Belt certification is a plus.
  • Experience with computer vision, time-series modeling, anomaly detection, predictive maintenance, natural language processing, or generative AI applications relevant to manufacturing and operations.
  • Experience with cloud data and analytics platforms such as Databricks, Snowflake, Microsoft Azure, or AWS.
  • Experience with data visualization and business-intelligence tools such as Power BI or Tableau.
  • Familiarity with production deployment and MLOps practices or platforms such as MLflow, Azure Machine Learning, or AWS SageMaker.
  • Experience working with IoT, equipment, historian, control-system, or high-frequency sensor data.
  • Familiarity with AI-assisted development tools such as GitHub Copilot, Windsurf, or similar environments.
Physical Job Requirements

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position.

The physical demands described within the Responsibilities section of this job description are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. For Office Roles: While performing the duties of this job, the employee is regularly required to be independently mobile. The employee is also required to interact with a computer and communicate with peers and co-workers. Contact your manager or local HR to understand the Work Conditions and Physical requirements that may be specific to each role.

Benefits & Compensation

MiniMed offers a competitive salary and flexible benefits package

At MiniMed, we put people first. A commitment to our employees lives at the core of our values: We recognize their contributions. They share in the success they help create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every stage of your career and life.

Salary ranges for U.S (excl. PR) locations (USD):$112,000.00 - $190,000.00

For roles located in California, Seattle WA, Washington DC, Boston MA, and New York City, the salary range is $112,000.00 - $190,000.00 USD.  

 

Actual compensation may vary based on factors including experience, education, certifications, skills, market conditions, internal equity, and geographic location. Compensation and benefits information pertain solely to candidates hired within the United States (local market compensation and benefits will apply for others)

 


 

This position is eligible for a short-term incentive called the Short Term Incentive (STI).

At MiniMed, we are committed to supporting the well-being and financial security of our employees. Regular employees working 20 or more hours per week are eligible for a robust benefits package, including health, dental, and vision insurance, as well as access to a Health Savings Account, Healthcare Flexible Spending Account, life insurance, long-term disability leave, and a dependent daycare spending account. In addition, all regular employees enjoy incentive plans, a 401(k) plan with company match, short-term disability coverage, paid time off and holidays, participation in our Employee Stock Purchase Plan, and access to our Employee Assistance Program. Eligible employees may also benefit from our Non-qualified Retirement Plan Supplement and Capital Accumulation Plan, subject to IRS minimum earnings requirements. Please note that “regular employees” refers to those who are not temporary staff, such as interns, and some benefits may not apply to employees in Puerto Rico.

For further details about our comprehensive benefits, we encourage you to visit the link below.

MiniMed Benefits Overview

About MiniMed

MiniMed is a full-stack insulin delivery company dedicated to supporting people living with diabetes through every step of their journey — when and how they need it. For more than 40 years, we’ve been committed to redefining what’s possible: intelligent dosing systems designed for real life, predictive insights that stay a step ahead, and always on support when it’s needed most. At the heart of everything we do is a simple Mission: to make every day a better day for people with diabetes.

 

Learn more about our business, and our mission here.

 

It is the policy of MiniMed to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, familial status, membership or activity in a local human rights commission, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, MiniMed will provide reasonable accommodations for qualified individuals with disabilities.

 

If you are applying to perform work for MiniMed in any position which will involve performing at least two (2) hours of work on average each week within the unincorporated areas of Los Angeles County, you can find here a list of all material job duties of the specific job position which MiniMed reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of a conditional offer of employment. MiniMed will consider for employment qualified job applicants with arrest or conviction records in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

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Pay
At MiniMed, we put people first. A commitment to our employees lives at the core of our values: We recognize their contributions. They share in the success they help create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every stage of your career and life. Salary ranges for U.S (excl. PR) locations (USD):$112,000.00 - $190,000.00For roles located in California, Seattle WA, Washington DC, Boston MA, and New York City, the salary range is $112,000.00 - $190,000.00 USD. Actual compensation may vary based on factors including experience, education, certifications, skills, market conditions, internal equity, and geographic location. Compensation and benefits information pertain solely to candidates hired within the United States (local market compensation and benefits will apply for others)
Location & working pattern

Northridge, California, United States of America

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