Senior Supply Chain Data Scientist: ML Forecasting

Primary Talent Partners, LLC; Sunnyvale (CA); On-site; USD 83,000 - 96,000; Full time

Benefits offered by this job

No PTO

ACA supplemental package available

Job summary

Primary Talent Partners is seeking a Senior Supply Chain Data Scientist for an on-site, contract role in Sunnyvale, CA. You will build and optimize machine learning and statistical models to improve demand forecasting and inventory decisions, enhancing overall supply chain responsiveness.

This 12-month W2 hourly engagement emphasizes Python and SQL modeling, ETL-driven data pipelines, and translating complex analyses into actionable stakeholder recommendations.

Qualifications

• Bachelor’s degree in a technical field with 5+ years of related work experience; OR Master’s 3+ years; OR Doctoral 0–2 years.
• Strong Python and SQL, with solid ML and DL experience.
• Experience with ETL, data engineering, statistics, time-series forecasting, feature engineering, hyperparameter optimization, and model validation.
• Ability to communicate analytical results to technical and non-technical audiences and iterate based on feedback.

Responsibilities

• Develop and optimize ML and statistical models, including time-series forecasting and hyperparameter optimization.
• Build data and ETL pipelines, create data visualizations, and automate model training, deployment, and monitoring using MLOps.
• Partner with stakeholders to translate analyses into actionable recommendations.
• Create AI agent pipelines to automate routines and support faster decision-making.

Skills

Python

SQL

Machine learning

Deep learning

ETL

Statistics

Time-series forecasting

Feature engineering

Hyperparameter optimization

Model validation

Communication

Education

Bachelor's degree

Master's degree

Doctoral degree

Tools

MLOps

Data pipelines

Job description

Primary Talent Partners is seeking a Senior Supply Chain Data Scientist for an on-site, contract role in Sunnyvale, CA. You will build and optimize machine learning and statistical models to improve demand forecasting and inventory decisions, enhancing overall supply chain responsiveness.

This 12-month W2 hourly engagement emphasizes Python and SQL modeling, ETL-driven data pipelines, and translating complex analyses into actionable stakeholder recommendations.