Summary
Overview
Work History
Education
Skills
Websites
Hackathon
Timeline
Generic
Nandesh Naik

Nandesh Naik

Summary

Dependable Machine Learning Engineer with 8+ years of working Experience. Expertise in machine learning, with extensive experience in Python and machine learning skills. Cooperative team player with a positive attitude.

Overview

9
9
years of professional experience

Work History

Lead Machine Learning Engineer

Yum Brands
04.2021 - Current
  • End-to-End ML Model Development & MLOps
    Designed, trained, and deployed scalable machine learning models across production environments. Owned the full modeling lifecycle—from feature engineering and experimentation to performance tuning, monitoring, and automated retraining—driving AI-powered forecasting and labor optimization for partners like KFC and Pizza Hut.
  • Robust Data Pipelines & Feature Engineering
    Built high-throughput, scalable data pipelines to efficiently process large-scale behavioral and transactional datasets. Engineered optimized feature extraction workflows using time-based attributes and aggregated order metrics to accelerate model training and inference across mission-critical systems.
  • Infrastructure, Monitoring & API Development
    Developed backend services and modular APIs using FastAPI for internal tooling and new product initiatives. Implemented Apache Pulsar-based producer/consumer systems and socket-based APIs for real-time notifications. Established logging, monitoring, and alerting workflows using Datadog and internal systems to proactively address data-quality issues and operational failures.
  • Leadership, Collaboration & Documentation
    Led cross-functional ML initiatives such as customer-facing chatbot platforms and MLOps pipelines, while mentoring junior engineers in machine learning best practices. Produced clear documentation of model architectures and workflows, and communicated technical insights to both engineering and business stakeholders.

ML Engineer

Wolters Kluwer
Pune
09.2016 - 04.2021
  • Facilitated the migration of an on-premises data warehouse to a cloud-based Redshift infrastructure, orchestrating the development of ETL processes and ensuring the seamless transition of SSRS reports to interactive Tableau visualizations.
  • Spearheaded the design and implementation of an autonomous web ticket resolution system, harnessing machine learning algorithms to resolve tickets without human intervention. Led the end-to-end development process, from algorithm design to integration with Salesforce ticketing systems.
  • Conducted in-depth analysis of outliers to optimize employee productivity, utilizing machine learning models to identify underperforming individuals relative to their team. Additionally, prototyped a dynamic Python integration with Tableau for real-time performance monitoring.
  • Engineered a robust pipeline for trending topics analysis, leveraging advanced natural language processing (NLP) techniques using NLTK and Spacy libraries to preprocess data before model ingestion.
  • Provided essential support to data scientists by assisting in data cleaning and analysis using industry-standard machine learning frameworks such as Pandas and Numpy.
  • Conducted a comprehensive proof of concept (POC) on Azure QnA Maker to streamline the training and evaluation process for machine learning models, optimizing user interactions and knowledge base management.
  • Designed and implemented a command-line utility for real-time monitoring of ETL job statuses, enabling proactive management and troubleshooting of data pipeline operations.

Education

Master Degree -

MCA GOA University
01.2016

BSC -

Computer Science
01.2013

Skills

  • Python & SQL
  • Kubernetes & Docker
  • GIT CI/CD
  • AWS
  • FAST API
  • Tableau

Hackathon

  • 2020- 1st Customer Innovation
  • 2019- 1st Customer Innovation
  • 2018- 3rd Machine Learning Best use

Timeline

Lead Machine Learning Engineer

Yum Brands
04.2021 - Current

ML Engineer

Wolters Kluwer
09.2016 - 04.2021

Master Degree -

MCA GOA University

BSC -

Computer Science

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