Senior Data Scientist

Job Summary:

• 10 years of strong technical background, including a deep understanding of AI concepts and methodologies.

• 3-5 years hands on experience with LLM (commercial and open source), LangChain, LlamaIndex, agentic AI, Retrieval Augmented Generation, and Vector Databases

• 3-5 years of experience with graph databases (Neo4J and Cypher would be a big plus

• Txt2sql hand on experience is a plus

• Programing languages such as Python and Java and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, Scipy, Pandas, etc

• Solid understanding of experimental design, hypothesis testing, and casual inference methods

• Experience working with agile methodologies and tools.

• A passion for innovation and a desire to push the boundaries of AI.

• Financial industry experience would be a plus.

Key Responsibilities:

Leverage 10+ years of technical expertise to design and implement AI solutions, including a comprehensive understanding of AI concepts and methodologies.

Utilize 3–5 years of hands-on experience with LLMs (both commercial and open-source), LangChain, LlamaIndex, agentic AI, Retrieval-Augmented Generation (RAG), and vector databases to develop and deploy advanced AI applications.

Apply 3–5 years of experience with graph databases, particularly Neo4j and Cypher, to model and query complex data structures effectively.

Required Skills and Experience:

Demonstrate proficiency in programming languages such as Python and Java, and utilize libraries/frameworks like TensorFlow, PyTorch, scikit-learn, SciPy, and Pandas for data analysis and machine learning tasks.

Apply solid understanding of experimental design, hypothesis testing, and causal inference methods to validate AI models and algorithms.

Collaborate within agile teams, utilizing agile methodologies and tools to deliver AI solutions efficiently.

Foster a passion for innovation, continuously exploring new AI techniques and methodologies to push the boundaries of AI capabilities.

Experience in the financial industry is advantageous, providing context for applying AI solutions in financial applications.

Preferred Qualifications:

Extensive experience in AI/ML, with a focus on LLMs, graph databases, and vector-based retrieval systems.

Proficiency in programming languages and AI/ML frameworks.

Strong analytical skills, with expertise in statistical analysis and experimental design.

Experience working in agile environments, with a collaborative approach to problem-solving.

Interest in the financial industry and its applications of AI technologies.

Education : BE/Btech/BCA/MCA or similar qualification