Data Scientist

JITO; India; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

JITO is looking for a skilled Data Scientist to join their team in Gurugram. You will have the opportunity to develop LLM-powered applications, work with advanced ML techniques, and contribute to innovative data-driven solutions.

The ideal candidate will possess strong skills in Machine Learning and Data Science, with practical experience in using AWS services like Amazon SageMaker and building end-to-end ML workflows. If you have a passion for AI and data analytics, we want to hear from you!

Qualifications

• 5–8 years of professional experience in Data Science or Machine Learning.
• Strong understanding of data preprocessing and model evaluation.
• Hands-on experience building and deploying ML models.

Responsibilities

• Develop LLM-powered applications using platforms like Amazon Bedrock.
• Contribute to Retrieval-Augmented Generation (RAG) pipelines.
• Implement simple autonomous agents or workflows in Agentic AI.

Skills

Machine Learning

Data Science

Statistical Analysis

Amazon SageMaker

MLOps

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

scikit-learn

TensorFlow

PyTorch

AWS (S3, Lambda)

Job description

Minfy Technologies • Gurugram • Posted 1 day ago • Updated 1 day ago

Job Type: FullTimePermanent

Location: Gurugram

Work Mode: Onsite

Experience: Management

Travel Requirements:

Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
• Strong academic foundation in statistics, probability, and machine learning
• Core Experience: 5–8 years of professional experience in Data Science, Machine Learning, or Applied AI
• Hands‑on experience building, training, and deploying ML models in production environments
• Strong understanding of data preprocessing, feature engineering, and model evaluation
• Experience working on end‑to‑end ML workflows under guidance of senior/principal team members
• Ability to translate business and product requirements into data‑driven solutions
• Machine Learning & MLOps
  • Practical experience using Amazon SageMaker for:
    • Model training and tuning
    • Model deployment and inference
  • Experience with common ML algorithms using scikit‑learn, TensorFlow, or PyTorch
  • Familiarity with MLOps concepts such as:
    • Model versioning
    • Experiment tracking
    • Basic monitoring and retraining workflows

Responsibilities

• Generative AI & LLMs
  • Hands‑on experience developing LLM‑powered applications using Amazon Bedrock or similar platforms
  • Experience building or contributing to Retrieval‑Augmented Generation (RAG) pipelines, including:
  • Document ingestion and chunking
  • Embedding generation
  • Similarity search using vector databases
  • Practical knowledge of prompt engineering, prompt tuning, and output evaluation
  • Understanding of common LLM failure modes such as hallucinations and grounding issues
  • Ability to evaluate LLM responses for accuracy, relevance, and safety
• Agentic AI (Growing Expertise)
  • Exposure to Agentic AI concepts and frameworks such as AgentCore
  • Experience implementing:
    • Simple autonomous agents or workflows
    • Multi‑step reasoning with predefined tools
    • Tool‑calling, agent orchestration, and workflow automation
  • Understanding the importance of guardrails, human‑in‑the‑loop mechanisms, logging, and observability for agent behaviour
  • Cloud Platform: Working knowledge of key AWS services, including:
  • S3
  • Lambda
  • R