Must Have Technical/Functional Skills
• Experience is developing Risk models using Supervised ML techniques.
• Exposure to Model performance metrics.
• Model Development experience in Python/PySpark is preferred.
• An experienced Data Scientist to lead end-to-end AI/ML solution design and implementation across a range of business domains in financial services.
• You will be responsible for architecting robust, scalable, and secure data science solutions that drive
• innovation and competitive advantage in the BFSI sector.
• This includes selecting appropriate technologies, defining solution blueprints, ensuring production readiness, and mentoring cross-functional teams.
• You will work closely with stakeholders to identify high-value use cases and ensure seamless integration of models into business applications.
• Your deep expertise in machine learning, cloud-native architectures, MLOps practices, and financial domain knowledge will be essential to influence strategy and deliver transformative business impact.
• Proficient in Python, scikit-learn, TensorFlow, PyTorch, HuggingFace.
• Strong BFSI domain knowledge.
• Experience with NLP, LLMs (GPT), and deep learning.
• Hands-on with MLOps pipelines and tools.
• Experience with graph analytics tools (Neo4j, TigerGraph, NetworkX).

Roles & Responsibilities
• Experience is developing Risk models using Supervised ML techniques.
• Exposure to Model performance metrics.
• Model Development experience in Python/PySpark is preferred.
• Lead data science teams through complete project lifecycles from ideation to production.
• Define standards, best practices, and governance for AI/ML solutioning and model management.
• Collaborate with data engineering, MLOps, product, and business teams.
• Oversee integration of data science models into production systems.
• Evaluate and recommend ML tools, frameworks, and cloud-native solutions.
• Guide feature engineering, data strategy, and feature store design.
• Promote innovation with generative AI, reinforcement learning, and graph-based learning.
• Knowledge of Spark, PySpark, Scala.
• Experience leading CoEs or data sc ience accelerators.

Salary Range: $135,000 to $150,000 per year