Principal Data Scientist – Advanced Machine Learning

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 Principal Data Scientist, you’ll influence by interacting with Data Sciences leaders, technical leaders outside of Data Sciences, business leaders, and other Data Sciences products leaders. You will perform within the scale and scope of your role by identifying the problem, being the architect of the solution, influencing the portfolio, contributing to Data Sciences’ and Target’s values by modeling, contributing, and elevating the culture. You’ll get the opportunity to use your deep expertise in multiple areas from the following: machine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, Deep Learning, Natural Language processing or computer vision. As you establish best practices/programming principles and advocate for best software engineering practices, you’ll drive adoption of the latest science methodologies across retail problems. You will perform end-to-end technical architecture for scalable and performant Data Science solutions and integrate patterns into technology applications. You’ll design and drive core data science modules to enable easy re-use across multiple products/models to ensure modeling consistency and determine technology strategy while articulating how technical strategy aligns with business goals. We’ll look for you to help in technology evaluation and selection, as well as in creating technical product architectures, negotiate with Product Owners (PO) to ensure that the team has bandwidth to identify, prioritize and eliminate technical debt, and partner with business teams to translate business challenges into technical solutions.

You’ll partner with product/business in identifying the relevant problems to solve in their domain and with other Principals and leaders in identifying and solving for cross-product/domain optimization opportunities. While you serve as a Data Sciences ambassador across the enterprise, we’ll look to you to showcase Data Science capabilities in broader Target forums and technical communities outside Target, invest in mentoring and career growth guidance for individual contributors and future technical leaders, and provide technical guidance to team and to leaders. Through your understanding of what other teams within Data Sciences do, you’ll identify opportunities to drive cross-product efficiencies, understand the dependency between various applications/business processes and opportunities from cross-product optimization and develop deep understanding of multiple product areas that are inter-connected. 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) and 9+ years of professional experience or equivalent industry experience

• PhD degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) is preferred

• 7+ years of experience in modeling and algorithm design

• Significant expertise in linear algebra, statistics, information theory, econometrics, time series modeling, especially in statistical inference, generalized linear models, Markov decision processes

• Highly proficient in Python, Scala, Kotlin and/or JVM ecosystem

• Deep understanding of data structures and algorithms 

• Ability to test and measure algorithms/models

• Excellent communication skills. Ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives