Lead Data Scientist-Stores

About us:

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.

Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.

Overview about TII:

At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

Pyramid overview:

A role with Target Tech’s Data Science team means the chance to develop and manage state of the art machine learning algorithms that use data at scale to automate and optimize decisions. 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 in Stores, Supply Chain Optimization, and Network Planning rely on.

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

Team Overview:

Our Stores Data Science team oversees the development of state-of-the-art mathematical techniques to solve key problems for Target’s Stores, such as identifying optimal tasks prioritizing work and sequence work for our teams to meet the dynamic guest demands. The team leverage machine learning, operations research and simulation to help design the future of how our stores work.

Position Overview:

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 scope of your role by defining solutions and beginning to identify problems to solve. You will contribute to Data Sciences’ and Target’s culture by modeling and contributing to the ways we work. There are several ways to use your expertise in one or more of the following areas: machine learning, probability theory & statistics, optimization theory, Simulation, Econometrics, and machine learning. We will look to you to own design and implementation of an algorithmic solution (e.g., predictions, optimization or simulations), 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 trade-offs 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.

About You:

• 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) and 6+ years of professional experience or equivalent industry experience

• Master’s degree in Quantitative disciplines (Science, Operations Research, Technology, Engineering, Mathematics)

• 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

Know More About us here:

• Life at Target- https://india.target.com/

• Benefits- https://india.target.com/life-at-target/workplace/benefits

• Culture- https://india.target.com/life-at-target/belonging