Job Description
JOB PROFILE:
- Design, develop and optimize machine learning algorithms and AI Models to enhance predictive capabilities for credit risk, fraud detection and operational efficiency.
- Interpret and translate business requirements from banking functions into data-driven, machine learning solutions.
- Execute full-cycle data workflows including acquisition, cleansing, transformation, and exploratory analysis to prepare structured datasets for modeling.
- Develop, train, and validate machine-learning models using techniques such as regression, classification, clustering, time series forecasting, and natural language processing.
- Evaluate model performance using statistical and technical metrics and implement iterative improvements for enhanced accuracy, scalability, and business relevance.
- Design and maintain robust MLOps pipelines, ensuring reliable model deployment, version control, performance monitoring, and retraining capabilities.
- Document all modeling procedures, including data sources, assumptions, validation approaches, and ethical considerations to ensure auditability and compliance.
- Collaborate closely with software developers, IT infrastructure units, and business process owners to ensure seamless integration and adoption of AI/ML systems.
- Monitor the evolution of AI/ML tools, frameworks, ethical guidelines, and best practices, and assess their applicability to the Bank’s operations.
- Design, build, train, and deploy machine learning models and AI solutions.
- Analyze large datasets to derive actionable insights and build predictive models
- Stay up-to-date with the latest AI/ML research, tools, and technologies.
Job Specification
REQUIRED JOB KNOWLEDGE/EXPERTISE:
- Proficiency in Python and machine learning libraries such as Scikit-learn, TensorFlow, Keras, PyTorch, Pandas, and NumPy
- Familiarity with big data processing platforms like Apache Spark, PySpark.
- Proficient in AI framework – LangChain
- Strong Understanding of Retrieval Augmented Generation (RAG) architecture.
- Strong Knowledge of vector database
- Knowledge on types of AI based on modern advancements
- Hands-on experience with MLOps tools, CI/CD pipelines, and version control systems (Git)
- Sound understanding of AI/ML governance, responsible AI, and data privacy regulations applicable in the Banking sector
MINIMUM QUALIFICATION AND REQUIREMENTS:
Senior Officer Level
Bachelor’s Degree in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 4 years of relevant work experience
OR
Master’s Degree in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 3 years of relevant work experience
Officer Level
Bachelor’s Degree in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 3 years of relevant work experience
OR
Master’s Degree in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 2 years of relevant work experience
Junior Officer Level
Bachelor’s Degree with minimum 50% marks or CGPA 2.5 in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 2.5 years of relevant work experience
OR
Master’s Degree with minimum 50% marks or CGPA 2.5 in the field of Computer Science/ Information Technology/ Computer Engineering/ Data Science with at least 1.5 years of relevant work experience
AGE LIMIT
For Officer and Senior Officer Level:
Male: Minimum 21 Years of age not exceeding 40 years as on application deadline
Female: Minimum 21 Years of age not exceeding 45 years as on application deadline
For Junior Officer Level:
Male: Minimum 21 Years of age not exceeding 35 years as on application deadline
Female: Minimum 21 Years of age not exceeding 40 years as on application deadline
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