Data Scientist

Job Description: 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.