Senior Research Scientist

NielsenIQ in Chennai, TN, is seeking a Senior Research Scientist with a data-centric approach to join its applied research and innovation team. This role is pivotal in analyzing data, researching advanced techniques, and developing, testing, supporting, and delivering proof-of-concepts to address complex, large-scale real-world challenges. The ideal candidate will possess a strong foundation in machine learning, deep learning, and the operationalization of AI/ML solutions, alongside expertise in process automation.

Key Responsibilities include developing and applying machine learning innovations with minimal supervision, understanding stakeholder requirements, and effectively communicating results and conclusions. You will conduct feasibility studies, analyze data to identify optimal solutions, and ensure ML solutions and source code are simple, scalable, reproducible, and maintainable to high-quality standards. Collaboration with technical colleagues for integration and deployment of ML solutions is essential, fostering a motivated and effective team environment.

Essential Qualifications include a Bachelor's degree in Computer Science or a related field, demonstrated senior experience in Machine Learning, Deep Learning, and other AI fields, and practical experience with large datasets, production-grade code, and ML operationalization. Proficiency in Exploratory Data Analysis (EDA), hands-on experience with datasets, ML models (PyTorch or TensorFlow), and evaluations is required. The ability to interpret scientific papers and translate ideas into executable code, coupled with strong analytical, problem-solving, and logical thinking skills, is crucial. Candidates must exhibit a proactive attitude, intellectual curiosity, persistence, excellent English communication skills, and the ability to meet deadlines. Technical proficiency in Python, PyTorch, Git, pandas, dask, polars, sklearn, Hugging Face, Docker, and Databricks is mandatory.

Desired Skills include a Master's degree or specialization courses in AI/ML, with a PhD being a significant advantage. Experience in MLOps (MLFlow, Prefect) and cloud-based AI/ML solution deployment (Azure preferred) is highly valued. Familiarity with Large Language Models (LLMs) and Generative AI, including prompt engineering and Retrieval-Augmented Generation (RAG), is beneficial. Experience with Robotic Process Automation, Time Series Forecasting, and Predictive Modeling is a plus. Practical knowledge of databases such as SQL, ElasticSearch, Pinecone, and Faiss, along with prior experience in retail, consumer goods, e-commerce, or FMCG products, would be advantageous.