Data Scientist

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.
- Solid 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.

📌 Data Scientist (SG DS&MLE) - Deloitte (Bengaluru)
🏢 Trigent Software
📍 Bengaluru