3874822-Lead Assistant Manager

As a Data Scientist, you will derive actionable insights from large, complex and unstructured data by developing AI/ML techniques. Development, optimization and evaluating as well as deploying them into production environments would be the key aspects of your role. You will have to collaborate seamlessly across teams to integrate data-driven solutions and maintain data governance compliance. Stay abreast of industry trends, contribute to thought leadership, and innovate solutions for intricate business problems. Responsibilities: Develop and deploy AI and statistical algorithms to extract insights and drive actionable recommendations from complex datasets. Design rigorous testing frameworks to evaluate model performance, validate results, and iterate on models to improve accuracy and reliability. Perform R&D by exploring and optimizing algorithms, methodologies, and technologies to tackle complex problems and drive innovation. Stay updated with the latest advancements in data science methodologies, tools, and technologies, and contribute to the team's knowledge base through sharing insights, attending conferences, and conducting research. Establishing and maintaining data governance policies, ensuring data integrity, security, and compliance with regulations. Qualifications: 2+ Years of prior analytics and data science experience in driving projects involving AI and Advanced Analytics. Strong expertise in Deep Learning frameworks, NLP/Text Analytics, SVM, LSTM, Transformers, Neural network. In-depth understanding and hands on experience in working with Large Language Models along with exposure in fine tuning open source models for variety of use case. Strong exposure in prompt engineering, knowledge of vector database, langchain framework and data embeddings. Strong problem-solving skills and the ability to iterate and experiment to optimize AI model behavior. Proficiency in Python programming language for data analysis, machine learning, and web development. Hands-on experience with machine learning libraries such as NumPy, SciPy, and scikit-learn. Excellent problem-solving skills and attention to detail. Ability to communicate effectively with diverse clients/stakeholders. Education Background: Bachelor’s in Computer Science, Statistics, Mathematics, or related field. Tier I/II candidates preferred.