Data Science I_SUPPORT SERVICES_0746_8147_1094934

Kotak Mahindra Bank; Bengaluru; Sur place; INR 600 000 - 900 000; Plein temps

Résumé du poste

Kotak Mahindra Bank in Bengaluru is seeking a Data Scientist I to leverage strong ML foundations, build models, and explore generative AI and LLMs for enterprise applications.

You will collaborate with product, engineering, and compliance teams to deliver scalable, secure AI solutions while following Responsible AI and regulatory guidelines.

Qualifications

• Bachelor’s or Master’s in CS/DS/Math/Stats or related field.
• 1–2 years hands-on ML/AI project experience.
• Proficiency in Python and ML libraries.
• Experience with LLMs and prompts; RAG concepts.
• Familiarity with MLOps tools and deployment.

Responsabilités

• Develop and maintain ML models and AI systems.
• Work with LLMs/SLMs for enterprise use cases.
• Implement guardrails, security, and governance.
• Collaborate with cross-functional teams.
• Document experiments and monitor performance.

Connaissances

Python

ML libraries

Deep learning

LLMs/SLMs

Prompt engineering

Fine-tuning

Quantization

Pruning

Distillation

Model risk

AI security

DLP

XAI tools

Privacy techniques

AIOps/MLOps

Docker

Git

MLflow

Airflow

Geospatial analytics

Formation

Bachelor’s/Master’s in ComputerScience, DataScience, Mathematics, Statistics

Outils

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

Description du poste

Job Description:

Job Description –DataScientist I

Role Overview

We are seeking a highly motivated DataScientist Iwith strong foundational knowledge in machine learning, modern AI techniques, and emerging Large Language Model (LLM) capabilities. The role requires hands‑on experience with model development, fine‑tuning, evaluation, and adherence to Responsible AI and regulatory guidelines (RBI/MeitY). You will collaborate with cross‑functional teams to build scalable, secure, and explainable AI systems that drive business value.

Key Responsibilities

1. Machine Learning & Statistical Modeling

• Develop and maintain ML models including propensity models, classification, regression, and clustering.
• Performdatacleaning, feature engineering, and exploratorydataanalysis.
• Build models using Python, SQL, and leading ML frameworks (TensorFlow, PyTorch, Scikit‑learn).

2. Generative AI & LLMs

• Work with Large Language Models (LLMs)and Small Language Models (SLMs)for enterprise use cases.
• Apply fine‑tuning, distillation, and model optimization techniques to adapt models to business needs.
• Create and manage syntheticdatapipelines for training and evaluation.

3. AI Agents & Workflows

• Assist in designing AI agentsand agentic workflows to automate decision‑making processes.
• Contribute to building AI-driven orchestration systems across business workflows.

4. Model Evaluation & Guardrails

• Implement LLM-as-a-Judge, evaluation frameworks, prompt tests, and model benchmarking.
• Apply model risk assessment and mitigation strategies as per enterprise AI governance.
• Implement security guardrails, including DLP controls and content safety filters.

5. Responsible AI & Compliance

• Ensure all models comply with:
  • RBI – Financial Regulation for Emerging Entities (FREE) guidelines
  • MeitY AI &DataGovernance Guidelines
• Integrate Privacy Preservation, Explainable AI (XAI), and Responsible AI techniques into model workflows.

6. Engineering & MLOps

• Participate in AIOps/MLOps processes: model deployment, monitoring, versioning, CI/CD.
• Document experiments, track model performance, and support reproducible ML pipelines.

7.DataEngineering & Domain Collaboration

• Work with structured, unstructured, and geospatialdatasets (a plus).
• Collaborate closely with product, engineering, analytics, and compliance teams to translate business problems into ML solutions.

Required Skills

• Strong proficiency in Python, ML libraries (scikit‑learn, pandas, NumPy), and deep learning frameworks.
• Knowledge of LLMs, SLMs, prompt engineering, and RAG concepts.
• Familiarity with fine‑tuning, quantization, pruning, and distillation methods.
• Understanding of model risks, adversarial ML, and mitigation strategies.
• Experience with AI/ML security, guardrails, and DLP principles.
• Understanding of XAI tools (SHAP, LIME, Integrated Gradients).
• Sound knowledge of Responsible AI, privacy techniques (DP, k-anonymity).
• Basic familiarity with AIOps/MLOps, Docker, Git, MLflow, Airflow (preferred).
• Exposure to geospatial analytics (nice to have).

Educational Background

• Bachelor’s/Master’s in ComputerScience,DataScience, Mathematics, Statistics, or related fields.

Experience Required

• 1–2 years of hands‑on experience in ML/AI projects, internships, research, or capstone projects.

Nice‑to‑Have

• Experience with LangChain, LlamaIndex, or other agent frameworks.
• Participation in AI/ML competitions (Kaggle, Hackathons).
• Knowledge of BFSI domain analytics (advantage but not mandatory).

Requirements: