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 algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on.    

Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, to elevate Target’s culture, and apply retail domain knowledge.

As a Senior Data Scientist, you will influence by interacting within the Data Sciences team and with Product teams, perform within the scale and scope of your role by implementing solutions, and contribute to Data Sciences’ and Target’s culture by modeling the culture. Through your understanding of the foundations and working principles of machine learning algorithms, linear algebra, probability theory, statistics, and optimization theory, you will perform data exploration and analysis (look at distributions, find anomalies, create simple visualizations, etc.) and implement algorithmic solution given specifications, while adhering to best practices in model development. We will look to you to understand and actively follow foundational programming principles (best practices, know about unit tests, code organization, basics of CI/CD etc.) and create a well-maintainable & tested codebase with relevant documentation. You will get the opportunity to develop in one or more approved programming languages (Java, Scala, Python, R), and learn and adhere to best practices in data analysis and data understanding.

As you follow agile processes, you will implement prototypes for individual components of software or data science solutions and understand and leverage basic data structures and algorithms in implementing solutions. You will evaluate multiple specified techniques for a defined problem and determine the most appropriate option from a performance perspective.

Leverage your high-level understanding in business domain to gain knowledge of high-level Target business priorities, strategic goals and their impact, as well as details of the specific business sub-problem you are focused on. You will collaborate with peers on their product and provide technical support, and document and present work to peers, and participate in code reviews and gain broader understanding of different components within the application. The exciting part of retail? It’s always changing! 

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 experience
• 3+ years of professional experience or equivalent industry 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
• 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
• Passion for solving interesting and relevant real-world problems using a 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. Ability to clearly tell data driven stories through appropriate visualizations, graphs and narratives
• Self-driven and results oriented; able to meet tight timelines
• Strong team player with ability to collaborate effectively across geographies/time zones