Data Scientist

Molex
Austin, TX, United States
17 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$160,000.0 - $200,000.0
Working hours
Regular working hours

Tech stack

Computer-Aided Design Artificial Intelligence Microsoft Azure Data Transmissions Data Infrastructure Extract Transform Load (ETL) Data Visualization Experimental Data Statistical Hypothesis Testing Python (Programming Language) Machine Learning NumPy
+12 more
Power BI Azure Machine Learning Signal Integrity SQL Databases Azure Data Factory Large Language Models Pandas Scikit Learn Modeling and Simulation Machine Learning Operations Azure Synapse Analytics Databricks

Job description

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.

Requirements

  • 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.

Benefits & conditions

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.

About the company

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., 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.

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