Data Scientist

7 days ago

Mumbai Mumbai Suburban Navi Mumbai, India Kiya Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Hi All,

We have an urgent opening for the role of Data Scientist for one of our leading Investment banking client in Mumbai

Experience range : 5- 7 years

Immediate - Serving notice

Responsibilities

Direct Responsibilities

  • Collaborate with business stakeholders to understand requirements and identify opportunities for AI-driven solutions
  • Take ownership of prototyping and productizing AI use cases using our in-house LLMs
  • Design, develop and deploy Retrieval Augmented Generation (RAG) pipelines to improve document search, customer support, compliance, or similar workflows
  • Implement and evaluate classification systems for use cases such as email classification, transaction categorization, risk scoring etc.
  • Analyze and prepare data, text extraction, feature engineering and annotation work as required
  • Work with engineering teams to integrate solutions into production environments
  • Document models, workflows and best practices for future projects
  • Stay up to date on development in GenAI, NLP and data science methods

Technical:

  • Proficiency in Python programming (Python 3.x)

  • Experience with data science tools and technologies, including:

  • Jupyter Notebooks for data exploration and prototyping

  • Pandas for data manipulation and analysis
  • NumPy for numerical computing and data processing

  • Scikit-learn for machine learning and model development

  • Database knowledge (relational and NoSQL databases)

  • Understanding of NLP fundamentals, experience with text processing, and use of popular libraries (e.g. HuggingFace, Transformers, spaCy)
  • Foundational knowledge of LLMs including prompt engineering, fine-tuning basics, and awareness of their strengths/limitations for banking use cases
  • Understanding of vector databases (e.g. FAISS, Chroma), embedding models, indexing and connecting retrieval to LLMs

  • Knowledge of data engineering principles and practices

  • Data warehousing

  • Data governance

  • Data quality

  • Experience with data cleaning, preprocessing, and feature engineering techniques, including handling missing data, data normalization, and data transformation

  • Familiarity with data storage solutions, such as data lakes, data warehouses, or cloud-based storage services
  • Knowledge of CI/CD pipelines and tools, such as Jenkins, GitLab CI/CD
  • Exposure to deploying models as REST APIs, basic use of containerization (Dockers)

If anyone is interested , please share your resumes to

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