Senior Data Scientist, AI/ML Data Backbone (Azure)

Flint Hills Resources

Austin, Fremont, Lisle (TX, CA, IL)

On-site

USD 160,000 - 200,000

Full time

14 days+
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Job summary

Molex is seeking a Data Scientist to own the data backbone of an Azure-based AI/ML platform in Austin. You will turn historical design and simulation results into clean datasets, validate model outputs, and enable trusted decisions with robust data foundations and dashboards.

You will collaborate with ML engineers, LLM engineers, and MLOps to keep data reliable, structured, and queryable, applying DOE and rigorous statistics to drive insights and trust in models.

Qualifications

  • 10+ years in data science, preferably with engineering, simulation, or scientific data.
  • Hands-on experience building and validating AI/ML models.
  • Strong Python and SQL skills with experience in Azure data tools.

Responsibilities

  • Build and maintain ETL pipelines (Azure Data Factory / Azure Databricks) to structure design parameters and simulation results for ML use.
  • Run statistical and exploratory analyses to identify design parameters driving performance.
  • Validate model outputs against ground-truth simulation results and flag data quality issues.
  • Track model and pipeline performance over time and build Power BI dashboards for data and model health visibility.
  • Apply DOE principles to sample the design space efficiently.

Skills

Python
SQL
Power BI
DOE
Statistics
Azure

Education

Master's degree in a technical field

Tools

Azure Data Factory
Azure Databricks
Azure Synapse
Power BI

Job description

Molex is seeking a Data Scientist to own the data backbone of an Azure-based AI/ML platform in Austin. You will turn historical design and simulation results into clean datasets, validate model outputs, and enable trusted decisions with robust data foundations and dashboards.

You will collaborate with ML engineers, LLM engineers, and MLOps to keep data reliable, structured, and queryable, applying DOE and rigorous statistics to drive insights and trust in models.

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