This listing doesn't post a salary. Most similar roles pay
$131,762–$197,187.
Based on 240 similar postings.
Employer
About Target
Target Corporation is a large-format general merchandise and grocery retailer offering a wide assortment of everyday essentials, apparel, home goods, and electronics through stores and online. Industry: General Merchandise Retail
Target currently has
62 open roles
on FindRole.
Listed pay typically runs
$98,000–$176,000
across 51 roles with salary data.
As a Sr Data Scientist - Global Supply Chain and Logistics, you will join the Target Data Sciences team to develop and manage state of the art predictive and prescriptive algorithms. You will work with fellow data scientists to iterate on optimization and machine learning models while collaborating with engineers to deploy these solutions in production at scale. Your daily work involves writing high-performant code, designing analytical solutions for supply chain decisions, and resolving trade-offs between model granularity and system reliability. The role requires expertise in operations research, simulation, and advanced statistical techniques like regression and time series forecasting. You will utilize Python, R, Kotlin, or Java to build tools, while utilizing SQL and Hive for production datasets. This role addresses complex supply chain problems including inventory, transportation, sourcing, distribution, fulfillment, and planning.
What does a Data Scientist earn in California?
Median $213878 from 88 postings across 32 companies.
Develop state-of-the-art predictive and prescriptive algorithms to automate and optimize supply chain decisions.
Create high-performant, scalable code for models that run daily across millions of inventory combinations.
Design and deploy machine learning and optimization models in production environments at scale.
Formulate and implement mathematical models including mixed-integer programming, stochastic dynamic programming, and reinforcement learning.
Build internal data tools and production datasets using SQL, Hive, or Python for research and experimentation.
Resolve trade-offs between model granularity, performance, reliability, and codebase usability.
Improve engineering standards, tooling, and processes to enhance overall system maintainability.
Translate complex data into actionable insights through visualizations and narratives for business partners.
What we're looking for
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.
Proficiency in predictive and prescriptive algorithms.
Proficiency in one or more programming languages including Python, R, Kotlin, or Java.
Expertise in formulating and implementing mathematical models such as mixed-integer programming, stochastic dynamic programming, and reinforcement learning.
Experience implementing advanced statistical techniques like regression, clustering, PCA, and time series forecasting.
Experience writing production datasets in SQL/Hive or building internal data tools using a scripting language like Python.
Python
Machine Learning
Artificial Intelligence
Natural Language Processing
SQL
NoSQL
Hadoop
Hive
EMR
Kafka
Spark
MySQL
R
SAS
Monte Carlo Simulation
Data Visualization
Grafana