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 Sciences - Supply Chain Optimization team leverages operations research, simulation, and machine learning to help Target makes intelligent 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. Our team aims to be inclusive, collaborative, highly motivated, smart, and humble!
In this role at Target as a Lead Data Scientist – Supply Chain Optimization, 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, deploy and productionize models 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
- Mentor and develop other data scientists and engineers
What we’re looking for:
- You have a strong knowledge of supply chain optimization – inventory, transportation, sourcing, distribution, fulfillment and planning
- You have a passion and technical skills for helping Target make data-informed decisions
- You possess strong computer science fundamentals and love rock-solid, well-structured, and efficient code: data structures, algorithms, programming and information retrieval
- You write understandable, testable Python code with an eye towards maintainability
- A passion for empirical research and answering hard questions with large scale data
- You are a strong communicator. Explaining complex technical concepts to the business and other data scientists/engineers is no problem for you
- You understand that simplicity is hard but key to achieving maintainability and to being able to continually deliver value to the business
- You have usability and convenience for business users in mind
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About you:
- 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent work experience
- PhD/MS in Operations Research, Industrial Engineering, Computer Science, Mathematics, Statistics, Physics or related quantitative field
- 5+ years of experience leading large-scale implementations of supply chain optimization, simulation and machine learning modeling at scale
- Demonstrated proficiency in one or more programming languages: Python, R, Kotlin or Java
- Demonstrated experience writing highly performant code and deploying algorithms in a production environment. Proficient in predictive and prescriptive algorithms
- Experience 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
- Passion for solving relevant real-world problems using a data science approach
- Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series), etc.
- Experience producing reasonable documents/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