Sr Applied Data Scientist - Supply Chain Optimization

Target; Sunnyvale (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Target Data Sciences is seeking a Sr Data Scientist for Global Supply Chain and Logistics in Sunnyvale. You will collaborate with fellow data scientists and engineers to develop and deploy optimization and machine learning models at scale, shaping end-to-end supply chain decisions for Target.

You will learn the retail business intimately, balance model complexity with performance, and deliver impactful data-driven insights to business and product partners while advancing engineering standards

Qualifications

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics, or related quantitative fields.
• 3+ years of experience leading large-scale implementations of optimization, simulation, machine learning and deep learning modeling at scale.
• Demonstrated experience writing highly performant code and deploying algorithms in a production environment.
• Proficient in one or more programming languages: Python, R, Kotlin, or Java.
• Expert at formulating and implementing mathematical models ranging from mixed-integer programming, stochastic dynamic programming and reinforcement learning.
• Experience in implementing advanced statistical techniques like regression, clustering, PCA, time series forecasting, etc.
• Proficient in application/software architecture (definition, process modeling, etc.).
• Experience writing production datasets in SQL/Hive or building internal/production data tools for research or experimentation in a scripting language like Python.
• Able to produce reasonable documents and narratives suggesting actionable insights.
• Excellent communication skills with an ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives.
• Self-driven and results oriented; able to meet tight timelines.
• Collaborative team player with ability to partner effectively across time zones.

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. Improve engineering standards, tooling, and processes.

Skills

Supply chain optimization

Computer science fundamentals

Code quality and testing

Data-driven storytelling

End-user focus

Ambiguity management

Attention to detail

Cross-time-zone collaboration

Education

PhD in Operations Research

MS in Industrial Engineering

MS in Computer Science

Tools

Python

R

Kotlin

Java

SQL/Hive

Job description

About us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

A role with Target Data Sciences means the chance to help develop and manage state of the art predictive and prescriptive algorithms that use data to automate and optimize decisions at scale. The Target Data Science – Global Supply Chain and Logistics team leverages operations research, simulation, and machine learning to help Target makes intelligent, end‑to‑end supply chain business decisions. This involves writing high‑performant, scalable code as well as designing analytical solutions to extract insights and to prescribe best courses of action.

You’ll work in an environment that provides the freedom and agility of a startup - with the security and vast resources of a large established company with continuous learning opportunities provided.

In this role at Target as a Sr Data Scientist – Global Supply Chain and Logistics, you will:

• Work closely with fellow data scientists to 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. Our models run many times a day for millions of combinations of stock keeping units and distribution networks
• 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. Improve engineering standards, tooling, and processes

What we're looking for:

• Strong knowledge of supply chain optimization – inventory, transportation, sourcing, distribution, fulfillment, planning, etc.
• Strong computer science fundamentals and love rock‑solid, well‑structured, and efficient code: data structures, algorithms, programming languages, and information retrieval
• Strong technical and communication skills to deliver with quality and evangelize technical solutions to business, product and engineering partners
• Ability to write understandable, testable code with an eye towards maintainability
• You constantly think about the end‑user for solutions you develop, and prioritize business impact over technical sophistication
• Ability to deal with ambiguity, and prioritize progress over perfection
• You have an eye for detail, and relentless curiosity for supply chain problems
• You have a knack for answering open questions with data
• You understand that simplicity is hard but key to achieving maintainability and to being able to continually deliver value to the business

Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

About you:

• PhD or MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics, or related quantitative fields
• 3+ years of experience leading large‑scale implementations of optimization, simulation, machine learning and deep learning modeling at scale
• Demonstrated experience writing highly performant code and deploying algorithms in a production environment. Proficient in predictive and prescriptive algorithms
• Proficient in one or more programming languages: Python, R, Kotlin, or Java
• Expert at formulating and implementing mathematical models ranging from mixed‑integer programming, stochastic dynamic programming and reinforcement learning
• Experience in implementing advanced statistical techniques like regression, clustering, PCA, time series forecasting, etc.
• Proficient in application/software architecture (definition, process modeling, etc.)
• Experience writing production datasets in SQL/Hive or building internal/production data tools for research or experimentation in a scripting language like Python
• Able to produce reasonable documents and narratives suggesting actionable insights
• Excellent communication skills with an ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
• Self‑driven and results oriented; able to meet tight timelines
• Collaborative team player with ability to partner effectively across time zones

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ Sunnyvale location the role is assigned to, and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.

Target will consider for employment qualified applicants with criminal histories in a manner consistent with the San Francisco and City of Los Angeles Fair Chance Ordinances.