Specialized Analytics Senior Analyst - Assistant Vice President

The Specialized Analytics Sr Anlst is a seasoned professional role.

This includes deep expertise in Deep Learning and Machine Learning algorithms, practical experience with Generative AI technologies and frameworks, and specialized skills in Prompt Engineering, Retrieval Augmented Generation (RAG), Langgraph, Langchain frameworks and Large Language Model (LLM) fine-tuning. Candidates must be adept at Generative AI solution design and implementation. Complementing this, strong data science technical skills are essential, encompassing proficiency in programming languages like Python, experience with data manipulation tools such as PySpark, SQL, and Hive, and the ability to handle data requirements, collection, processing, cleaning, exploratory data analysis, and effective data visualization. A solid understanding of analytical and statistical foundations, including hypothesis testing, segmentation, predictive modeling, and performance optimization, is also crucial.

Beyond technical expertise, the role requires significant leadership and management capabilities, including the ability to lead, mentor, and develop a team of data scientists. Strategic acumen is paramount, demanding a candidate who can demonstrate strategic thinking and vision, identify emerging trends, challenge the status quo, and drive innovation to set ambitious business goals. Excellent communication and stakeholder management skills are also vital for effectively translating complex technical concepts and performance metrics for senior business audiences and ensuring strong collaboration with both team members and business partners. Apart from these, they should also have the following skillset:

Responsibilities:

• Lead the architecture, design, and development of mission-critical, production-grade Generative AI applications and Agentic solutions, ensuring they are scalable, reliable, and secure.

• Define and own the technical roadmap for AI platforms, making critical decisions on architecture, technology stacks, and long-term evolution.

• Drive the strategy for designing and redesigning business processes with Agentic solutions, focusing on advanced agent architecture, memory management, hallucination control, and reinforcement learning-based feedback loops.

• Champion and enforce best practices for compliance, security, MLOps, and Model Governance across all AI projects.