Job description

Your Job The Data Scientist will own the data backbone of our Azure-based AI/ML engineering platform. They will be turning historical design and simulation results into clean, structured datasets, and statistically validating that the AI/ML models built on top of them can be trusted before they inform design decisions. Our Team Established in 1938, Molex delivers comprehensive electronic solutions for various markets, including data communications, telecommunications, consumer electronics, industrial, automotive, commercial vehicle, aerospace and defense, medical, and lighting. You'll join the platform team behind our Azure AI/ML engineering tools, working closely with ML engineers, LLM engineers, and MLOps teams to keep the data foundation reliable and query-able. What You Will Do • Build and maintain ETL pipelines (Azure Data Factory / Azure Databricks) that structure engineering design parameters and simulation results for ML use. • Run statistical and exploratory analysis to identify which design parameters most strongly drive performance outcomes. • Validate model outputs against ground-truth simulation results, and flag data quality issues that could bias downstream models. • Track model and pipeline performance over time; build Power BI dashboards giving engineering teams visibility into data and model health. • Apply DOE (design of experiments) principles to help sample the design space efficiently rather than exhaustively. Who You Are (Basic Qualifications) • Hands-on experience building and validating AI/ML models — not just data prep or descriptive analytics. • 10+ years in a data science role, ideally with engineering, simulation, or scientific/experimental data. • Strong Python (pandas, NumPy, scikit-learn) and SQL. • Comfortable with Azure data tools (Azure Data Factory, Azure Databricks, Azure Synapse) or an equivalent cloud data stack. • Solid statistics grounding: hypothesis testing, regression, DOE, variance/sensitivity analysis. • Experience with data visualization/dashboarding tools (Power BI or similar). What Will Put You Ahead • Signal integrity or RF/high-speed electronics knowledge. • Experience validating ML model outputs (drift detection, error analysis) in a cloud ML platform. • Familiarity with CAD/engineering design data or PLM systems. • Experience working alongside ML engineering teams on shared cloud data infrastructure. For this role, we anticipate paying $160,000 - $200,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy. Hiring Philosophy All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here . Who We Are As a Koch company, Molex is a leading supplier of connectors and interconnect components, driving innovation in electronics and supporting industries from automotive to health care and consumer to data communications. The thousands of innovators who work for Molex have made us a global electronics leader. Our experienced people, groundbreaking products and leading-edge technologies help us deliver a wider array of solutions to more markets than ever before. At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company. Our Benefits Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength - focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes - medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter. Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results. Equal Opportunities Equal Opportunity Employer, including disability and protected veteran status. Except where prohibited by state law, some offers of employment are conditioned upon successfully passing a drug test. This employer uses E-Verify. Please click here for additional information. (For Illinois E-Verify information click here , aquí , or tu ).

Requirements

Must-haves

Build and maintain ETL pipelines (Azure Data Factory / Azure Databricks) that structure engineering design parameters and simulation results for ML use.
Run statistical and exploratory analysis to identify which design parameters most strongly drive performance outcomes.
Validate model outputs against ground-truth simulation results, and flag data quality issues that could bias downstream models.
Track model and pipeline performance over time; build Power BI dashboards giving engineering teams visibility into data and model health.
Apply DOE (design of experiments) principles to help sample the design space efficiently rather than exhaustively.
Who You Are (Basic Qualifications)
Hands-on experience building and validating AI/ML models — not just data prep or descriptive analytics.
10+ years in a data science role, ideally with engineering, simulation, or scientific/experimental data.
Strong Python (pandas, NumPy, scikit-learn) and SQL.
Comfortable with Azure data tools (Azure Data Factory, Azure Databricks, Azure Synapse) or an equivalent cloud data stack.
Solid statistics grounding: hypothesis testing, regression, DOE, variance/sensitivity analysis.
Experience with data visualization/dashboarding tools (Power BI or similar).
What Will Put You Ahead
Signal integrity or RF/high-speed electronics knowledge.
Experience validating ML model outputs (drift detection, error analysis) in a cloud ML platform.
Familiarity with CAD/engineering design data or PLM systems.
Experience working alongside ML engineering teams on shared cloud data infrastructure.
Hiring Philosophy
All Koch companies value diversity of thought, perspectives, aptitudes, experiences, and backgrounds. We are Military Ready and Second Chance employers. Learn more about our hiring philosophy here .

Nice-to-haves

For this role, we anticipate paying $160,000 - $200,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

azureaimlllmpythonsql

Platform: avature
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

Parental Leave