Data Scientist – Manufacturing & Supply Chain Intelligence

Data Scientist – Manufacturing & Supply Chain Intelligence

Location:

Fremont, CA – Hybrid

Role Overview

We are looking for an experienced

Data Scientist

to build and enhance advanced machine learning solutions supporting manufacturing and supply chain intelligence.

This role will focus on developing and tuning a

Cognitive Intelligence layer

, including

Normal Behavior Models, anomaly detection, entity resolution, should-cost models, predictive analytics, and human-in-the-loop learning

.

The ideal candidate will have strong hands-on experience building production-grade machine learning models and improving model accuracy based on business-user feedback and overrides.

Key Responsibilities

• Design, build, and tune

machine learning and predictive models

for enterprise use cases.

• Develop

Normal Behavior Models

to identify unusual patterns, anomalies, and deviations in business or operational data.

• Build and improve

anomaly detection models

for manufacturing, supply chain, procurement, or operational datasets.

• Develop

entity resolution and matching models

to identify, consolidate, and connect related entities across multiple data sources.

• Build

should-cost and predictive cost models

to support pricing, procurement, sourcing, or cost intelligence use cases.

• Analyze large and complex datasets to identify trends, patterns, relationships, and business insights.
• Incorporate

human-in-the-loop feedback

into machine learning models.

• Retrain and refine models based on user overrides, corrected confidence scores, and business feedback.
• Continuously evaluate model performance, accuracy, confidence levels, and effectiveness.
• Partner with engineering, product, supply chain, procurement, manufacturing, and business teams to understand requirements and translate them into analytical solutions.
• Support deployment, monitoring, validation, and continuous improvement of machine learning models in production environments.
• Document model logic, assumptions, methodology, results, and performance metrics.

Required Qualifications

• Master's or PhD in

Data Science, Statistics, Computer Science, Machine Learning, Mathematics, Engineering

, or another related quantitative field.

• 4+ years of experience

applying machine learning, deep learning, NLP, or advanced analytics in an enterprise environment.

• Strong hands-on experience developing and tuning

machine learning models

.

• Experience with

anomaly detection or Normal Behavior Models

.

• Experience developing

predictive models or should-cost/cost estimation models

.

• Experience with

entity resolution, entity matching, record linkage, or data matching techniques

.

• Experience incorporating

human feedback, overrides, or corrections into model retraining and improvement cycles

.

• Strong understanding of model evaluation, confidence scoring, feature engineering, and model optimization.
• Strong analytical and problem-solving skills with the ability to work with complex and large datasets.
• Experience working with cross-functional technical and business teams.

Preferred Qualifications

• Experience within

manufacturing, semiconductor, supply chain, procurement, sourcing, or industrial analytics

.

• Experience working with supplier, material, procurement, manufacturing, or cost-related datasets.
• Exposure to production machine learning environments and model monitoring.
• Experience with advanced statistical modeling, NLP, deep learning, or AI-based decision-support systems.