Target is an iconic brand, a Fortune 50 company and one of America’s leading retailers.
Global Supply Chain and Logistics at Target is evolving at an incredible pace. We are constantly re-imagining how we get the right product to the right guest better, faster and more cost effectively than before across 1900 locations
A role with the Target Data Science and Analytics team means building scalable data science products in support of the ever-
changing supply chain landscape. This will mean being more intelligent, automated and algorithmic in our decision-making.
Evaluating product flow from vendor to distribution center, and to the stores across the first mile, middle mile and last mile, with focus on inventory modeling and replenishment, to improve operating efficiencies both within 4 walls of distribution center and across the network.
So, we’re looking for exceptional people who are proactive, creative, independent, innovative and comfortable working in varying degrees of ambiguity.
Are you a creative problem-solver who seeks root cause, simplifies problems, quickly identifies solutions, commits to a plan and then positively influences others to execute it?
If so, you will have success on this dynamic team.
Develop a strong understanding of Target supply chain and logistics data and work on analytical projects supporting first, middle and last mile delivery.
The role involves working closely with clients and internal teams to deliver high quality, end-to-end analytical solutions that create strong business impact.
Work hands on and actively partner across the team defining business problem, data discovery to insights / predictions
Understand the business problem, identify the key challenges, formalize the problem algorithmically, and prototype solutions
Anticipate and Evaluate impact of analytical solutions on related projects as part of the developing complex analytical algorithm / solutions for various business problems
Work with data engineers on data quality assessment, data cleansing and data analytics.
Perform exploratory and targeted data analyses using descriptive statistics and other methods
Ability to develop and deploy scalable and reproducible analytical models for answering variety of business problems
Build self-service tools for error detection, diagnosis and predictive metrics.
Work on developing optimization / statistical / Discrete event simulation models to answer problems for replenishment, inventory positioning / planning, product flow etc
Ability to test and analyze the prototype results on Target data, actively engage with business partners to identify improvement areas and implement enhancements based on statistical analysis and business logic
Generate analyses, annotated code, and other project artifacts to document, archive, and communicate work and outcomes.
Master’s degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience from a reputed tier 1 education institutes like IITs, ISI, IISc etc.
5-8 years of relevant experience
Good Knowledge and experience developing optimization, simulation and statistical models,
Strong analytical thinking skills. Ability to creatively solve business problems, innovating new approaches where required.
Background in supply chain will be preferable but not mandatory
Strong hands on programming skills in Python, SQL, Hadoop / Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory
Good working Knowledge of Mathematical and statistical concepts, MILP, algorithms and computational complexity, data analysis, data mining, forecasting / predictive modeling, simulations, visualizations, machine learning, etc.
Passion for solving interesting and relevant real-world problems using Data science approach
Experience in implementing advanced statistical techniques like regression, clustering, PCA, forecasting (time series) etc.
Able to produce reasonable documents / narrative suggesting actionable insights
Excellent communication skills
Self-driven and results oriented. Willing to stretch to meet tight timelines.
Strong team player with ability to collaborate effectively across geographies / time zones