Ravi Kadakkottil

Data Scientist / Machine Learning Engineer

Bangalore, India 2+ yrs exp 85 · Excellent

About

Data Scientist / Machine Learning Engineer with 2+ years building, evaluating, and deploying ML and Deep Learning models for real-world business problems, including credit risk scoring (classification) for banking and predictive maintenance (time-series forecasting, anomaly detection) for energy. Skilled across the full ML lifecycle: preprocessing, feature engineering, training, hyperparameter tuning, cross-validation, evaluation, deployment, and monitoring on Azure ML. Also builds production Generative AI applications — LLM agents, RAG, embeddings, and vector search — using LangChain, LangGraph, and Azure OpenAI. Proficient in Python, SQL, R, PyTorch, TensorFlow, Scikit-learn. M.Tech in AI & Data Analytics from NIT Calicut.

Skills & Expertise (55)

Python Advanced

8.1/10

Years Exp

Exploratory data analysis Advanced

8.1/10

Years Exp

NumPy Advanced

8.1/10

Years Exp

Pandas Advanced

8.1/10

Years Exp

Hugging Face Advanced

8.1/10

Years Exp

Prompt Engineering Advanced

8.1/10

Years Exp

Vector Databases Advanced

8.1/10

Years Exp

Embeddings Advanced

8.1/10

Years Exp

Retrieval Augmented Generation Advanced

8.1/10

Years Exp

LangGraph Advanced

8.1/10

Years Exp

LangChain Advanced

8.1/10

Years Exp

Azure OpenAI Advanced

8.1/10

Years Exp

Large Language Models Advanced

8.1/10

Years Exp

Azure ML Advanced

8.1/10

Years Exp

Azure AI Foundry Advanced

8.1/10

Years Exp

Model Monitoring Advanced

8.1/10

Years Exp

Model Evaluation Advanced

8.1/10

Years Exp

Cross-Validation Advanced

8.1/10

Years Exp

GitHub Advanced

8.1/10

Years Exp

Hyperparameter Tuning Advanced

8.1/10

Years Exp

Git Advanced

8.1/10

Years Exp

Feature Engineering Advanced

8.1/10

Years Exp

scikit-learn Advanced

8.1/10

Years Exp

FastAPI Advanced

8.1/10

Years Exp

REST APIs Advanced

8.1/10

Years Exp

KQL Intermediate

7.1/10

Years Exp

Matplotlib Intermediate

7.1/10

Years Exp

Power BI Intermediate

7.1/10

Years Exp

Statistical Methods Intermediate

7.1/10

Years Exp

Flask Intermediate

7.1/10

Years Exp

Docker Intermediate

7.1/10

Years Exp

Probability Theory Intermediate

7.1/10

Years Exp

Linear Algebra Intermediate

7.1/10

Years Exp

Azure DevOps Intermediate

7.1/10

Years Exp

Databricks Intermediate

7.1/10

Years Exp

Microsoft Fabric Intermediate

7.1/10

Years Exp

PyTorch Intermediate

7.1/10

Years Exp

SQL Intermediate

7.1/10

Years Exp

Regression Intermediate

7.1/10

Years Exp

Classification Intermediate

7.1/10

Years Exp

Supervised Learning Intermediate

7.1/10

Years Exp

Unsupervised Learning Intermediate

7.1/10

Years Exp

Decision Trees Intermediate

7.1/10

Years Exp

XGBoost Intermediate

7.1/10

Years Exp

Random Forest Intermediate

7.1/10

Years Exp

Feature Selection Intermediate

7.1/10

Years Exp

Anomaly Detection Intermediate

7.1/10

Years Exp

TensorFlow Intermediate

7.1/10

Years Exp

Keras Intermediate

7.1/10

Years Exp

CNNs Intermediate

7.1/10

Years Exp

RNNs Intermediate

7.1/10

Years Exp

LSTMs Intermediate

7.1/10

Years Exp

Transformers Intermediate

7.1/10

Years Exp

agentic AI Intermediate

7.1/10

Years Exp

Time-Series Analysis Intermediate

7.1/10

Years Exp

Work Experience

Associate Data Scientist

NeoStats Analytics Solutions

May 2025 - Present

Built and deployed classification models for credit risk scoring in banking and time-series forecasting models with anomaly detection for predictive maintenance in the energy sector, using feature engineering, hyperparameter tuning, and cross-validated evaluation to improve prediction accuracy and reliability. Led end-to-end Machine Learning pipelines - data pre-processing, feature engineering, model training, evaluation, deployment, and monitoring - on Azure ML, following MLOps best practices. Designed and deployed Generative AI applications and LLM-based agents using Azure OpenAI, LangChain, and LangGraph, implementing Retrieval Augmented Generation (RAG) and multi-agent workflows, with structured evaluation of outputs for accuracy and reliability. Developed FastAPI REST APIs to expose Machine Learning and AI services to downstream applications. Built real-time data ingestion pipelines and live Power BI/KQL dashboards, enabling business stakeholders to monitor KPIs with sub-minute latency. Presented model outputs and analytical findings to non-technical business stakeholders, translating results into actionable insights for banking digital-journey optimization.

Data Science Intern

NeoStats Analytics Solutions

May 2024 - May 2025

Developed enterprise Generative AI and LLM applications using Azure OpenAI, LangChain, FastAPI, and Azure Document Intelligence for unstructured document processing. Built real-time data ingestion and analytics systems on Microsoft Fabric using KQL and event-driven architectures. Designed interactive Power BI dashboards for business intelligence reporting across multiple industry verticals.