Senior Data Scientist, Hybrid: Supply Chain Optimization

Relha LLC; Sunnyvale, Northern (CA, KY); Hybrid; USD 98,000 - 211,000; Full time

Benefits offered by this job

Hybrid work arrangement

Health benefits

401(k)

Job summary

Target in Sunnyvale, CA is seeking a Sr Applied Data Scientist in Supply Chain Optimization. You will collaborate with fellow data scientists to review optimization and machine learning algorithms and develop state-of-the-art mathematical models that drive end-to-end supply chain decisions.

You will deploy algorithms in production at scale, work with engineers, and partner with business teams to translate data into actionable insights, balancing model granularity, performance, and

Qualifications

• PhD or MS in Industrial Engineering, Operations Research, Computer Science, Applied Mathematics, Statistics, Physics or related quantitative fields.
• 3+ years of experience leading large-scale implementations of optimization, simulation, machine learning and deep learning at scale.
• Extensive experience writing highly performant Python code and deploying algorithms in a production environment.

Responsibilities

• Review and iterate on optimization and machine learning algorithms and develop state of the art mathematical models.
• Collaborate with engineers to design and deploy algorithms in production at scale.
• Work with business partners to learn about the retail business and processes in play.
• Ideate and resolve tradeoffs between model granularity and features as well as performance, reliability, and usability of our codebase.

Skills

Optimization

Python

Operations Research

Machine Learning

SQL

Education

PhD or MS in quantitative field

Tools

Python

SQL/Hive

Pandas/Numpy

Job description

Target in Sunnyvale, CA is seeking a Sr Applied Data Scientist in Supply Chain Optimization. You will collaborate with fellow data scientists to review optimization and machine learning algorithms and develop state-of-the-art mathematical models that drive end-to-end supply chain decisions.

You will deploy algorithms in production at scale, work with engineers, and partner with business teams to translate data into actionable insights, balancing model granularity, performance, and