Lead Data Scientist - RecommendationsFull time
As a Fortune 50 company with more than 350,000 team members worldwide, Target is an iconic brand and one of America’s leading retailers. Every time a guest enters a Target store or browses Target.com, they experience the impact of Target’s investments in technology and innovation. We’re the technologists and data scientists behind one of the most loved retail brands delivering joy to millions of our guests! Join our global in-house technology team of more than 4,000 engineers, data scientists, architects, coaches, and product managers striving to make Target the most convenient, safe, and joyful place to shop. We use agile practices and leverage open-source software to adapt and build best-in-class technology for our team members and guests—and we do so with a focus on diversity and inclusion, experimentation, and continuous learning.
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 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 and to elevate Target’s culture and apply retail domain knowledge.
As a Lead Data Scientist, you’ll influence by interacting with the Data Sciences team, Product teams, Scientist/Engineer individual contributors from other pillars, and business partners. You will perform within the scale and scope of your role by defining solutions and beginning to identify problems to solve and contribute to Data Sciences’ and Target’s culture by modeling and contributing to the culture. You’ll get the opportunity to use your expertise in one or more of the following areas: machine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, Deep Learning, Natural Language processing or computer vision. We will look to you to own design and implementation of an algorithmic solution (e.g., recommendation or forecasting algorithm), including data understanding, feature engineering, model development, validation and testing, and deployment to a production environment. You’ll drive development of problem statements that capture the business considerations, define metrics/measurement to validate model performance, and drive feasibility study with data requirements and potential solutions approaches to be considered. You’ll evaluate tradeoffs of simple vs complex models/solutions in determining the right technique to employ for a business problem and develop and maintain a nuanced understanding of the data generated by the business, including fundamental limitations of the data. You’ll leverage your proficiency in one or more approved programming languages (Java, Scala, Python, R), and ensure foundational programming principles in developing code (best practices, writes unit tests, code organization, basics of CI/CD etc.) are followed in developing the team’s products/models.
You’ll not only stitch together basic data pipelines for a given problem and own design and implementation of individual components within Data Science/Tech applications, but also articulate the technical strategy, value of technology, and impact on the business. As you do so, you’ll collaborate with engineers, scientists, and business partners/product owners to create algorithmic solutions that are performant and integrated into applications. We’ll look to you to mentor and provide technical support within a team, including mentoring junior team members, and present your work and your team’s work to business partners and other Data Sciences teams. With a deeper understanding of your functional area of responsibility, you’ll support agile ceremonies, collaborate with peers across multiple products, communicate and collaborate with business partners, and demonstrate an understanding of areas outside your scope of responsibility. 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.
- 4-year degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics) and 6+ years of professional experience or equivalent industry experience
- Master’s degree in Quantitative disciplines (Science, Tech, Engineering, Mathematics)
- 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
- Experience solving 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 create 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
- MS or PhD in a quantitative field
- Experience with recommender systems