Lead Data Scientist

Posted:
9/5/2024, 12:13:27 AM

Location(s):
Karnataka, India

Experience Level(s):
Senior

Field(s):
AI & Machine Learning ⋅ Data & Analytics

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 diverse 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 diverse 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 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 is expected to develop highly performant code for Model Performance, and to elevate Target’s culture and apply retail domain knowledge. 

 

As a Lead Data Scientist, you’ll be interacting with the Data Sciences team, Product teams, Scientist/Engineer, individual contributors from other pillars, and business partners. You will develop solutions and identify problems to solve and contribute to Data Sciences’ and Target’s culture by modeling and contributing to the product within your scope and scale. You’ll get the opportunity to use your expertise in one or more of the following areas: Machine Learning, Application of Probability/Statistics, Optimization, 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, deployment to a production environment and monitoring. 

 

Team Overview 

For this specific role, you will be responsible for building and maintaining models supporting Target’s pricing decisions across stores and digital- so a good understanding of retail pricing is important. Along with the cross functional team you will work on generating price recommendations for Target’s assortment spanning across frequency and discretionary business. You will be interacting with business and product partners (along with UI/UX & data engineers) to understand the requirements and tailor the model architecture. Given the scale of the problem, it is imperative to understand software design principles. You are required to write efficient and scalable code, diagnose model results, review summary statistics and iteratively improve the quality. 

 

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 (Python, R, Kotlin, Spark), 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. We’ll look at 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. 

 

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, Technology, Engineering, Mathematics)  

  • 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, Spark. Additional knowledge of Scala, R, Java, Kotlin desired but not mandatory  

  • Experience in implementing statistical techniques like regression (linear & non-linear), clustering, PCA etc.  

  • Strong experience building and scaling price elasticity & forecasting models 

  • Hands on experience in optimization techniques like linear programming, integer programming, nonlinear optimization, and dynamic programming etc. 

  • Experience on Reinforcement Learning algorithms is preferred, but not mandatory 

  • 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 

 

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