Senior Data Scientist, Supply Chain Optimization — Hybrid

1114 Target Enterprise Inc; Sunnyvale (CA); Hybrid; USD 98,000 - 211,000; Full time

Benefits offered by this job

Health benefits

401(k)

Employee discount

Paid time off

Job summary

Target is seeking a Sr Data Scientist – Supply Chain to design and implement predictive and prescriptive models for end-to-end supply chain optimization. You will work with data scientists and engineers to deploy scalable algorithms and translate complex data into actionable insights for business partners.

Ideal candidates have 3+ years leading large-scale optimization and ML projects, strong Python skills, and a solid foundation in CS and quantitative methods.

Qualifications

• PhD or MS in Industrial Engineering, Operations Research, Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field.
• 3+ years leading large-scale implementations of optimization, simulation, ML and DL at scale.
• Extensive experience writing highly performant Python code and deploying algorithms in production.
• Proficient in predictive and prescriptive algorithms; strong data storytelling skills.

Responsibilities

• Review and iterate on optimization and machine learning algorithms and develop state of the art models.
• Collaborate with engineers to deploy algorithms in production at scale.
• Work with business partners to understand the retail processes involved.
• Balance model granularity with performance, reliability and usability of code.
• Improve engineering standards, tooling, and processes.

Skills

Supply chain optimization

CS fundamentals

Python coding

Data storytelling

Communication skills

Ambiguity management

End-user focus

Education

MS/PhD in quantitative field

Tools

Python

SQL/Hive

Job description

Target is seeking a Sr Data Scientist – Supply Chain to design and implement predictive and prescriptive models for end-to-end supply chain optimization. You will work with data scientists and engineers to deploy scalable algorithms and translate complex data into actionable insights for business partners.

Ideal candidates have 3+ years leading large-scale optimization and ML projects, strong Python skills, and a solid foundation in CS and quantitative methods.