Senior Data Scientist

Tata Consultancy Services; São Paulo; Hybrid; BRL 180,000 - 320,000; Full time

Benefits offered by this job

Health, dental, and life insurance

Meal and transportation vouchers

Gympass

24/7 support through TCS Cares

Cultural, wellness, and recreational,

Job summary

Tata Consultancy Services seeks a Senior Data Scientist to design, develop, and optimize advanced AI, ML, and Data Science solutions for the energy trading domain. The role emphasizes LLMs, Agent Engineering, RAG, predictive analytics, time-series modeling, and AI governance to enable intelligent automation and data-driven outcomes.

The Senior Data Scientist will collaborate with Trading, Business, Product, Data Engineering, and Technology teams to build AI-powered models, dashboards, and

Qualifications

• 5+ years in data science, ML, or AI projects.
• StrongPython and data libraries experience.
• SQL and PostgreSQL proficient.
• Experience building ETL/ELT pipelines.
• Hands-on with LLM APIs and prompt engineering.
• Knowledge of RAG and vector search techniques.
• Experience with vector databases and retrieval optimization.
• Familiarity with MLOps, deployment, and monitoring.

Responsibilities

• Design and implement RAG architectures using business data.
• Develop AI agents for strategic recommendations and forecasting.
• Evaluate LLMs from various providers and open-source models.
• Implement prompt engineering and agent orchestration strategies.
• Apply Explainable AI to improve transparency of recommendations.
• Build models to measure trading performance and operational metrics.
• Perform exploratory data analysis to identify trends and opportunities.
• Create dashboards, KPIs, and analytics for decision making.
• Design vector search architectures using embeddings.
• Monitor model performance, drift, and production reliability.
• Support MLOps including deployment, retraining, and governance.
• Collaborate with Data Engineering on scalable data pipelines.
• Document experiments, datasets, and model outcomes.

Skills

Pandas

NumPy

Scikit-learn

SQL

PostgreSQL

ETL/ELT

LLM APIs

Prompt engineering

RAG architectures

Vector search

Embeddings

LangChain

MLOps

Cloud platforms

Time-series analysis

Model evaluation

Python

Tools

pgvector

Pinecone

Weaviate

ChromaDB

LangChain

LangGraph

AutoGen

CrewAI

Semantic Kernel

MLflow

Databricks

SageMaker

Vertex AI

Job description

TCS is seeking a Senior Data Scientist to design, develop, and optimize advanced AI, Machine Learning, and Data Science solutions that support strategic decision-making within the energy trading domain. The role focuses on Large Language Models (LLMs), Agent Engineering, Retrieval-Augmented Generation (RAG), predictive analytics, time-series modeling, and AI governance to enable intelligent automation and data-driven business outcomes.

The Senior Data Scientist will collaborate closely with Trading, Business, Product, Data Engineering, and Technology teams to build AI-powered solutions, analytical models, and intelligent recommendation systems. The position requires strong expertise in Data Science, Machine Learning, LLMs, MLOps, and cloud-based AI architectures.

Key Responsibilities:

• Design and implement Retrieval-Augmented Generation (RAG) architectures using operational and historical business data.
• Develop AI agents for strategic recommendations, historical comparisons, forecasting, and performance monitoring.
• Evaluate and benchmark LLMs including OpenAI, Anthropic, and open-source models.
• Design and implement prompt engineering, prompt optimization, and agent orchestration strategies.
• Implement Explainable AI (XAI) frameworks to improve transparency and auditability of AI-generated recommendations.
• Build analytical models to measure trading effectiveness, purchasing strategies, and operational performance.
• Perform exploratory data analysis to identify trends, risks, anomalies, and business opportunities.
• Develop dashboards, reports, KPIs, and advanced analytics for decision-making.
• Design and implement vector search architectures using embeddings and retrieval frameworks.
• Monitor AI model performance, drift detection, and production reliability.
• Support MLOps processes including deployment, versioning, retraining, monitoring, and governance.
• Collaborate with Data Engineering teams to build and maintain scalable data pipelines.
• Document experiments, methodologies, datasets, evaluations, and model outcomes.
• Support solution architecture, production deployments, and cloud-based AI initiatives.

Required Skills & Qualifications:

• 5+ years of experience in Data Science, Machine Learning, or Artificial Intelligence projects.
• Hands‑on experience with Pandas, NumPy, Scikit‑learn, and related Data Science libraries.
• Experience with SQL and PostgreSQL.
• Experience building ETL/ELT pipelines and data engineering workflows.
• Hands‑on experience with LLM APIs, prompt engineering, and model evaluation.
• Experience designing and implementing RAG architectures.
• Knowledge of chunking, embeddings, vector search, reranking, and retrieval optimization techniques.
• Experience with vector databases such as pgvector, Pinecone, Weaviate, ChromaDB, or similar technologies.
• Experience applying evaluation frameworks such as RAGAS, LLM-as-a-Judge, DeepEval, or equivalent solutions.
• Experience with AI agent frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent.
• Experience with time‑series analysis and forecasting models.
• Strong analytical thinking, statistical modeling, and problem‑solving skills.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience with MLOps practices, model versioning, deployment, monitoring, and retraining pipelines.
• Experience with production AI systems and enterprise‑scale deployments.
• Experience with monitoring, observability, and AI performance management.
• Advanced English communication skills.

Preferred Skills:

• Experience in deregulated energy markets, energy trading, or commodity trading.
• Experience reducing hallucinations and improving reliability in RAG-based systems.
• Experience with AI workflow observability tools.
• Experience with MLflow, Databricks, SageMaker, Vertex AI, or equivalent MLOps platforms.
• Experience applying Explainable AI (XAI) methodologies.
• Experience with fine‑tuning LLMs and domain adaptation techniques.
• Experience working with offshore and global teams.
• Open-source contributions related to AI, Machine Learning, Data Science, or Data Engineering.

Location: Curitiba (Hybrid - 3 days onsite / 2 days remote) OR Londrina (Onsite)

Health, dental, and life insurance, meal and transportation vouchers, childcare assistance, Gympass, and 24/7 support through TCS Cares (psychological, legal, social, and financial assistance). Access to cultural, wellness, and recreational programs through the TCS-SESC partnership.

Global career opportunities through access to the latest technologies, world-class learning platforms, professional certifications, and mentorship programs designed to accelerate your growth and future-ready skills.

Tata Consultancy Services is an equal opportunity employer. Our commitment to diversity and inclusion drives us to provide equal opportunities to all candidates who meet our required knowledge and competency needs, regardless of socio-economic background, race, color, national origin, religion, sex, gender identity, age, marital status, disability, sexual orientation, or any other protected characteristic.