AI Engineer/ Data Scientist

Job Title: AI / Gen-AI Data Scientist

Role Summary

AI / Gen-AI Data Scientist

Key Responsibilities

• Develop, fine-tune, and deploy

  AI/ML & Generative AI models

  for NLP, text analytics, and predictive solutions.
• Build

  data pipelines, perform feature engineering

  , and ensure data quality for model training & inference.
• Collaborate with cross-functional teams to

  translate business problems into AI solutions

  .
• Implement

  ML Ops practices

  (model versioning, monitoring, deployment pipelines).
• Conduct

  exploratory data analysis & statistical modelling

  to derive actionable insights.
• Experiment with

  LLMs/SLMs

  ,

  prompt engineering

  ,

  fine-tuning

  approaches for BFSI-specific use cases.

Must-Have Tech Stack

• 4–8 years of

  proven experience

  as a Data Scientist / AI Engineer.
• Strong proficiency in

  Python

  with libraries:

  Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch

  .
• Expertise in

  NLP & LLMs

  (Hugging Face, LangChain, RAG pipelines, prompt engineering).
• Solid understanding of

  machine learning algorithms, deep learning, and statistical methods

  .
• Experience in

  data preprocessing, feature engineering

  , and building end-to-end ML pipelines
• Experience with

  ML Ops frameworks

  (MLflow, DVC) for model lifecycle management.

Good-to-Have Skills

• Prior exposure to

  BFSI projects

  (fraud detection, risk modelling, compliance automation).
• Familiarity with

  cloud AI/ML platforms

  (AWS SageMaker, Azure ML, GCP Vertex AI).
• Knowledge of

  vector databases

  (FAISS, Pinecone, Weaviate) for retrieval-augmented generation.
• Exposure to

  data engineering tools

  (Spark, Databricks, Airflow, Kafka).
• Experience with

  data visualization tools

  (Tableau, Power BI, Matplotlib, Seaborn).
• Awareness of

  Responsible AI / Explainable AI

  practices.