Data Scientist

Job Title:

Company: Futran Solutions

Experience:

About Us

Futran Solutions is a next-generation digital acceleration company delivering end-to-end digital transformation and technology services across industries like BFSI, Insurance, Retail, Education, Healthcare, Food, and Manufacturing.

Role Overview

Data Scientist

Key Responsibilities

• Design, train, and evaluate ML models for

  classification, anomaly detection, forecasting, and NLP tasks

  .
• Build and fine-tune

  deep learning models

  (RNN, LSTM, GRU, Transformers like BERT, GPT, T5).
• Develop

  Generative AI solutions

  including RAG pipelines for document search, Q&A, and summarization.
• Apply

  model optimization techniques

  (e.g., quantization) for performance improvement in production.
• Fine-tune LLMs using

  SFT, LoRA, QLoRA

  for domain-specific tasks.
• Monitor

  model drift

  , retrain models, and track evaluation metrics.
• Collaborate with

  data engineering, backend, and DevOps teams

  for production deployment using CI/CD.
• Maintain clean, reproducible code and proper documentation.

Required Skills

• 4–5 years of experience in

  Machine Learning/Data Science

  roles.
• Strong proficiency in

  Python

  ,

  ML/DL libraries

  (scikit-learn, pandas, PyTorch, TensorFlow).
• Hands-on experience with

  Transformer models

  and

  open-source LLMs

  (Hugging Face).
• Familiarity with

  Generative AI tools

  and

  RAG frameworks

  (LangChain, LlamaIndex).
• Experience in

  model quantization

  (dynamic/static, INT8) and deployment in constrained environments.
• Knowledge of

  vector databases

  (FAISS, Pinecone, Azure AI Search) and embeddings.
• Proficiency in

  model evaluation

  , deployment, and performance tuning.
• Familiarity with

  Docker, MLflow, CI/CD pipelines

  .

Preferred Qualifications

• Experience in

  LLM fine-tuning

  (SFT, LoRA, QLoRA).
• Exposure to

  MLOps platforms

  (SageMaker, Vertex AI, Kubeflow).
• Knowledge of

  distributed data processing

  (Spark) and orchestration tools (Airflow).
• Contributions to

  research papers, blogs, or open-source projects

  in ML/NLP/GenAI.