below marketmost similar roles pay hereabove market
This role pays more than
79%
of similar roles. Most pay
$159,093–$228,425
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$194k
for comparable roles.
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
94 open roles
on FindRole.
Listed pay typically runs
$98,000–$176,000
across 66 roles with salary data.
As a Principal Data Scientist - Supply Chain Network Planning and Design, you will serve as a senior technical leader shaping advanced analytics and operations research capabilities for long-term supply chain strategy. You will architect optimization models, simulations, digital twins, and forecasting solutions to inform network and capital investment decisions regarding footprint, capacity, inventory, product flow, and transportation. Your daily work involves owning the decision capability roadmap, leading agile scrum routines, and mentoring data scientists to elevate technical rigor. You will utilize Python, SQL, and optimization solvers like Gurobi, CPLEX, and Pyomo, alongside cloud computing, machine learning, and AI. This role solves complex, ambiguous problems at enterprise scale by translating strategic business needs into scalable analytical solutions and operationalizing models into decision-support tools.
What does a Data Scientist earn?
Median $173200 from 345 postings across 65 companies.
Architect optimization models, simulations, and digital twins to support network footprint and transportation decisions.
Apply advanced operations research and data science methods to solve complex supply chain problems at enterprise scale.
Establish technical standards for model architecture, validation, scalability, and reproducibility.
Own and evolve the decision capability roadmap to align analytical investments with long-term network strategy.
Lead team scrum routines including sprint planning, backlog refinement, and daily stand-ups.
Partner with cross-functional teams to translate complex business challenges into scalable analytical solutions.
Mentor data scientists and elevate technical rigor across the analytics team.
Operationalize models into scalable decision-support tools in partnership with Engineering and Product teams.
What we're looking for
PhD or MS in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, Statistics, Data Science, or related quantitative industry experience.
Extensive experience in supply chain, logistics, transportation, or large-scale network design.
8+ years of experience applying operations research, mathematical optimization, simulation, or advanced analytics to complex business problems at scale.
Deep expertise in optimization and quantitative modeling with proficiency in Python, SQL, and optimization solvers like Gurobi, CPLEX, or Pyomo.
Experience architecting scalable analytical models and decision-support capabilities.
Demonstrated ability to define technical roadmaps, prioritize analytical investments, and lead agile delivery.
Strong systems thinking, technical judgment, and ability to influence senior leaders and global teams.
Experience mentoring technical talent and driving cross-functional alignment.
Python
SQL
Machine Learning
Optimization Models
Spark
Scala
R
scikit learn
TensorFlow
Data Visualization
Statistics
Operations Research
Econometrics
AI
Python
Mathematical Optimization
Mixed-Integer Programming
Simulation
Monte Carlo
Forecasting
Uncertainty Quantification
Stochastic Programming
Bayesian Decision Methods
Reinforcement Learning
AI/ML
Data Science
Version Control
Data Integration
Digital Twins
Python
SQL
Machine Learning
Natural Language Processing
ETL
ELT
Data Modeling
Oracle Analytics Cloud
Tableau
Power BI
Oracle Fusion Cloud Applications
Predictive Analytics
Cloud Computing
Distributed Systems
Data Pipelines