Lead Data Scientist - Advanced Machine Learning

Job Description

Lead Data Scientist About us: Overview about TII At Target, we have a timeless purpose and a proven strategy. And that hasnt 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 Targets global team and has more than 4,000 team members supporting the companys global strategy and operations. A role with Target Data Science & Engineering 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, youll be challenged to harness Targets impressive data breadth to build the algorithms that power solutions our partners in in Marketing, Supply Chain Optimization, Network Security and Personalization rely on Team Overview Our Generative AI team oversees the development of a platform which will allow various product & engineering teams to leverage GenAI based solutions in an eEective manner.We also support various teams within Target so that they will be able to build productsas per Target standards regarding use of responsible AI. As a Lead Data Scientist at Target, you will get an opportunity to design, develop, deploy and maintain data science models and tools. Youll work closely with applied data scientists, data analysts and business partners to continuously learn and understand evolving business needs. Youll also collaborate with AI/ML engineers and data scientists on peer teams to build and productionize groundbreaking GenAI based solutions for various teams. Position Overview Analyze large datasets for insights leading to business process improvements or solution development. Contribute to the research, design, and implementation of leading-edge generative AI technologies to address and solve complex problems that contribute to finding solutions for the retail world. Work with Multimodal LLMs, enhance model performance, fine-tune LLMs Work with the team to build and maintain complex software systems and tools. Adopt modular architecture and good software development/engineering practices to enhance the overall product performance and guide other team members. Produce clean, efficient code based on specifications. Coordinate the analysis, troubleshooting and resolution of issues in the models and software. Requirements: Bachelors/MS/PhD in Mathematics, Statistics, Computer Science, or other related fields. 8+ years of relevant experience. Ability to lead by example a group of Data Scientists. Strong analytical thinking. Ability to creatively solve business problems, innovating innovative approaches where required. Ability to clean, transform, manipulate, and analyze large datasets for insights leading to business process improvements or solution development. Experience in developing, testing, and maintaining large codebases in a collaborative environment, while meeting industry best practices. Highly proficient in programming skills in Python, SQL, Hadoop/Hive. Exposure to programmatic use of GenAI/LLMs and related ecosystem. Experience in developing Deep Learning based solutions using PyTorch or TensorFlow Self-driven and results oriented. Willing to stretch to meet tight timelines. Strong team player with ability to collaborate eEectively across geographies/ time zones. Excellent written and verbal communication skills Preferred Qualifications: Knowledge of containerized solutions using Docker/ Kubernetes. Exposure to Prompt Engineering, Embedding Generation, Retrieval Augmented Generation(RAG) space (e.g., Vector DB, Elastic Search) will be plus. Knowledge of Computer Vision & Deep Learning Methods. Good working Knowledge of Mathematical and statistical concepts, optimization, data structures and algorithms, data analysis, visualizations, and applications of same in a variety of business problems. Experience deploying solutions with large-scale business impact in commercial