Data Scientist

Deloitte Shared Services India; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Deloitte Shared Services India in Bengaluru seeks an experienced ML/AI engineer to design and deploy scalable data science solutions, including RAG pipelines, chatbots, and intelligent assistants. You will build data pipelines, collaborate in Agile teams, and ensure robust model validation and deployment.

The role requires strong Python, ML, and API development skills, plus a solid grounding in statistics, data quality, and observability practices for ML/LLM systems.

Qualifications

• Proficiency in Python and ML development for data-intensive environments.
• Experience with data processing, cleansing, and validation for analytics.
• Strong knowledge of statistical modelling: regression, clustering, decision trees, logistic regression.
• Familiarity with ML algorithms (KNN, Random Forests, Ensemble Methods).
• Experience with LLM basics and prompt engineering concepts.

Responsibilities

• Leverage ML and data analysis experience to support business objectives.
• Guide model development, validation, and performance evaluation.
• Design and develop ML and LLM-based solutions including RAG pipelines and chatbots.
• Develop and integrate REST APIs and FastAPI-based services for deployment.
• Support observability and monitoring for ML/LLM systems.
• Build and maintain data pipelines for ingestion, preprocessing, transformation and validation.
• Collaborate in Agile Scrum teams and contribute to iterative development.
• Document processes, models, APIs, and technical implementations clearly.

Skills

Python

Machine Learning

SQL

Data processing

Exploratory Data Analysis

Statistical modelling

ML algorithms

LLMs basics

Prompt engineering

Vector databases

LangChain/Semantic Kernel

Data visualization

Agile/Scrum

Tools

REST API development

FastAPI

Git

API design

Job description

JD

Responsibilities:

• Leverage strong machine learning and data analysis experience in complex data environments to support business objectives in effective and scalable ways.


• Utilize a solid foundation in mathematics and statistics to guide model development, validation, and performance evaluation.


• Design and develop machine learning and LLM-based solutions, including applications such as RAG pipelines, chatbots, and intelligent assistants where applicable.


• Develop and integrate REST APIs and FastAPI-based services for model deployment and application integration.


• Support implementation of monitoring and observability practices for ML and LLM systems, including performance tracking and response evaluation.


• Build and maintain data pipelines, including data ingestion, preprocessing, transformation, and validation.


• Collaborate effectively within Agile Scrum teams, contributing to iterative development and continuous improvement.


• Document business processes, workflows, models, APIs, and technical implementations clearly and comprehensively.


• Engage with business and technical stakeholders to understand requirements and translate them into data science and AI solutions.


• Participate in collaborative conceptualization sessions to brainstorm and refine ML and LLM-based solutions.


• Assist in implementing agent-based workflows using modern frameworks and support integration with enterprise systems.

Mandatory Skills:

• Proficiency in Python, Machine Learning, REST API development, FastAPI, and SQL.


• Experience with data processing, cleansing, and validation to ensure data quality and integrity for analysis.


• Conduct data quality checks and exploratory data analysis to support model development.


• Demonstrated programming skills in Python and experience in building and integrating APIs.


• Build end-to-end machine learning models, including data preparation, feature engineering, and deployment workflows.


• Strong understanding of statistical modelling techniques such as Regression, Clustering, Decision Trees, and Logistic Regression.


• Familiarity with machine learning algorithms such as KNN, Random Forests, Ensemble Methods, and probabilistic approaches.


• Basic experience with Large Language Models such as GPT, BERT, or similar architectures.


• Understanding of prompt engineering and LLM application usage.


• Familiarity with vector databases, embeddings, and retrieval-based approaches.


• Basic understanding of agent frameworks such as LangChain or Semantic Kernel.


• Knowledge of data mining concepts and experience with data visualization tools and dashboards.

Preferred Skills:

• Experience working with Large Language Models and building simple LLM-based applications.


• Understanding of natural language processing (NLP) techniques and their application in business contexts.


• Familiarity with agent-based workflows and orchestration concepts.


• Basic knowledge of Model Context Protocol (MCP) or similar agent communication standards.


• Exposure to monitoring and observability practices for ML and LLM systems.


• Familiarity with RAG architectures and document retrieval pipelines.


• Exposure to advanced topics such as deep learning, transformers, and fine-tuning approaches.


• Ability to integrate ML and LLM solutions into larger product or business workflows.


• Identify opportunities to automate data processing, analysis, and business workflows using ML and LLM techniques.


• Propose hypotheses and conduct experiments to solve business problems using data-driven approaches.

Additional Responsibilities:

• Stay updated with the latest advancements in machine learning, LLMs, and AI tools.


• Contribute to team knowledge sharing and adoption of best practices in ML and LLM development.


• Support senior team members in building scalable, reliable, and efficient AI systems.


• Ensure data quality, consistency, and reliability across all data science workflows.


• Follow responsible AI practices, including fairness, explainability, and compliance standards.