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Senior Data Scientist

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Onsite

Senior Data Scientist

Ganit Business Solutions

Senior Data Scientist

Skills

PythonData SciencepandasGitMachine LearningAIAWSNLP / Natural Language Processing

1 month ago

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Important information


Contract type:

Permanent

Location:

Mumbai, Maharashtra, India

Work mode:

Onsite

Published on:

18 September 2026

What they need


About Ganit Inc

  • Founded by senior industry experts, Ganit is the fastest-growing data science company in Chennai with offices in Bengaluru, Mumbai & New Jersey.
  • Ganit has flipped the data science value chain. We don't start with a technique. For us, consumption comes first. With this philosophy we have successfully scaled from being a small start-up to 200 resource company with clients in the US, Singapore, Africa, UAE, and India.
  • We are helping Fortune 500 companies across the globe to maximize their Decision-Making Power (#DMP). We are looking for experienced data enthusiasts who can make data talk to them.

Job Overview:

We are looking for a highly skilled and self-motivated Generative AI Engineer with over 5 years of experience to join our dynamic Data Science team. The ideal candidate will bring deep expertise in Generative AI, along with a solid foundation in Data Science. You should have hands-on experience in designing, deploying, and managing Large Language Model (LLM)-based solutions, developing intelligent AI agents, and delivering scalable AI applications on cloud platforms. In this role, you will be instrumental in building end-to-end intelligent systems that drive tangible business impact across diverse domains.

Key Responsibilities:

Qualifications:

  • Bachelors or Master’s degree in Computer Science, Data Science, AI, or a related field.

  • 5+ years of hands-on experience in machine learning and data science.

  • Proficient in Python and ML libraries (scikit-learn, pandas, Hugging Face Transformers, etc.).

Generative AI & LLMs

  • Lead, Design, fine-tune, and deploy Large Language Models (LLMs) using platforms such as AWS Bedrock and open-source model hubs.
  • Build and manage autonomous AI agents using frameworks like LangGraph, Crew AI, Phidata, AutoGen, or AWS Bedrock Agents.
  • Implement Retrieval-Augmented Generation (RAG) pipelines with vector databases (e.g., Pinecone, FAISS, PGVector) to enhance contextual responses.
  • Conduct LLM evaluations using prompt engineering techniques and custom fine-tuning to optimize performance for business use cases.
  • Evaluate model performance using appropriate metrics and optimize for accuracy, efficiency, and scalability.
  • Stay updated with the latest research in Gen AI and integrate relevant innovations into ongoing projects.
  • Contribute to model governance, interpretability, and responsible AI practices.

Programming & Software Engineering

  • Write clean, modular, and well-documented Python code, leveraging machine learning libraries and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
  • Deploy AI agents on cloud platforms with a focus on user experience, including building lightweight front-end interfaces using tools like Streamlit or Gradio.
  • Use Git for version control, collaborating through pull requests, code reviews, and CI/CD workflows.
  • Adhere to software engineering best practices, including testing, code modularity, and documentation for maintainability and scalability.

Teamwork & Communication

  • Collaborate with cross-functional teams including data engineers, product managers, and business stakeholders to deliver AI-driven solutions.
  • Translate complex technical concepts into clear insights for both technical and non-technical audiences.
  • Manage multiple projects simultaneously, ensuring timely delivery and high-quality outputs.

Must have - Data Science & NLP

  • Develop and deploy supervised ML models including regression, classification, and time-series forecasting.
  • Apply NLP techniques for text classification, sentiment analysis, and named entity recognition.
  • Use vector embeddings for similarity search and information retrieval tasks.

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