Nishant Kadian
Senior Data Scientist- Immediate Joiner
GTA,ON
Summary
Data Scientist with 5 years of industry expertise and an MSc in Data Science. Expertise in delivering ChatBot and NLP-driven business solutions using advanced LLMs like Llama, GPT, Mistral, BERT, and Generative AI techniques like RAG, PEFT. Proficient in the Python-based machine learning lifecycle, including data handling, feature engineering, model building, evaluation, and deployment on cloud platforms (GCP, AWS, Azure). Adept at managing a wide range of databases, from traditional SQL to NoSQL (MongoDB, Solr) and vector databases such as ChromaDB.
Overview
6
6
years of professional experience
36
36
years of post-secondary education
Work History
Senior Data Scientist
HT Media Ltd
11.2023 - Current
- Engineered LLM-Powered Recommendation System: Developed and implemented a recommendation engine for recruiters by finetuning the LLAMA2-7B Large Language Model using PEFT technique, increasing their engagement on the portal by 21%. Tech used: LLAMA2-7B LLM, PEFT LLM Fine-Tuning, XGBoost, AWS, Flask.
- RAG + GPT-4 LLM Chatbot Implementation: Designed a chatbot for Shine Learning using the Retrieval-Augmented Generation (RAG) technique with GPT-4 LLM, enhancing user experience by providing real-time assistance to job seekers. Tech used: RAG, Langchain, GPT-4 LLM, LangServe.
- Personalized Job Recommendations: Created an algorithm for job seekers, boosting candidate logins and activity on the job portal by 25.3%. Tech used: Gemma-7B LLM, Vector DB (Chroma DB), MongoDB, Python.
- Advanced Computer Vision system: Developed a computer vision algorithm to extract and filter out unwanted photos from resumes.Tech used: Vision Transformer,YOLO, MTCNN, ChromaDB.
- Automated Leads Generation Data Pipeline : Built an end-to-end data pipeline for lead generation, improving lead quality and efficiency, resulting in a 45% increase in sales. Tech used: Python, BigQuery, Solr, SQL, AWS S3.
Deputy Manager- Data Sciences
WNS Global Services
04.2022 - 11.2023
- GLM ML Model predicting Claim Loss:Engineered a precise GLM Machine Learning model for predicting claim loss costs, enabling accurate premium calculation and enhancing customer satisfaction, resulting in an 8.1% increase in policy renewal rate.Technology used: GLM, Python, R, SQL
- Reviews Sentiment Analysis: Conducted Sentiment Analysis (NLP) on customer reviews of claim settlements, providing actionable insights that improved customer satisfaction strategies. Technology used: SBERT, PyTorch, OpenAI-ChatGPT, Langchain, Python.
- Team Leadership: Led a team of 6 junior data scientists, mentoring and guiding them to achieve project goals, resulting in improved team performance and successful project deliveries.
Data Scientist
Mahindra Teqo
09.2021 - 04.2022
- Advanced Machine Learning Model : Created a Machine Learning model to predict clipping loss in solar power plant inverters, and finally deployed the model on Azure using Flask API framework. The project boosted the power output of plant by 1.78%. Tech used: Machine Learning ( Clustering, XGBoost, Random Forest, SVM), Python, Azure, Django, Gunicorn, Nginx.
Consultant-Technology Consulting Practice
Ernst & Young
02.2021 - 09.2021
- Policy Non-Persistency Prediction Model: Developed and deployed a Machine Learning model on AWS to predict whether a potential customer will pay the premium at the first-year renewal. This model API was consumed by underwriters to identify the risky customers at the time of policy application. Tech used: Machine Learning (XGBoost, Deep Learning,Random Forest, SVM), SQL, Python, Excel, AWS, Flask, Gunicorn, Nginx.
- Policy Lapse Prediction Model: Co-developed and deployed an ML model using XGBoost and Deep Learning techniques to predict policy lapse probabilities (Policyholder not paying premium within 6 months of due date), to identify high-risk policyholders well in advance and take proactive actions accordingly. Tech used: Machine Learning (XGBoost, Deep Learning,Random Forest, SVM), SQL, Python, Excel, AWS, Flask, Gunicorn, Nginx.
Associate Data Scientist / Data Scientist
Flip Robo Technologies
06.2020 - 02.2021
- Advanced Face Recognition System: Developed and deployed a face recognition system using advanced CNN architectures such as FaceNet, VGGFace and adaptive similarity threshold algorithm, to identify individuals accurately. Tech used: Computer Vision, CNN,FaceNet, VGG-Face, Tensorflow, Keras
Fin & Admin Business Associate
IBM
05.2018 - 01.2019
- Textual Data Cleaning Pipeline: Contributed to a text categorization project by developing a data-preprocessing pipeline, enhancing the model´s accuracy in categorising products based on textual descriptions. Tech used: Python, NLTK,NLP.
Education
Master of Science - Data Science
Liverpool John Moores University
04.2001 - 04.2021
Bachelor of Technology - Computer Science
Guru Gobind Singh Indraprastha University
04.2001 - 04.2017
Skills
- Large Language models: (LLMs) & Gen-AI (RAG, Llama, Gemma, GPT, BERT, Langchain, Huggingface, PEFT, LangChain,Transformers), Python
- Machine Learning: (Linear Regression, Decision Trees, Random Forest, XGBoost, Clustering)
- Databases: (SQL, MongoDB, ChromaDB)
- DeepLearning: (Tensorflow, Pytorch, Keras)
- Cloud Models deployment: (GCP, AWS, Azure)
- Natural Language Processing
- Computer Vision ( YOLO, MTCNN, FaceNet)
- Recommendation System
- MLOps(Flask, Gunicorn, Nginx)
Websites
Timeline
Senior Data Scientist
HT Media Ltd
11.2023 - Current
Deputy Manager- Data Sciences
WNS Global Services
04.2022 - 11.2023
Data Scientist
Mahindra Teqo
09.2021 - 04.2022
Consultant-Technology Consulting Practice
Ernst & Young
02.2021 - 09.2021
Associate Data Scientist / Data Scientist
Flip Robo Technologies
06.2020 - 02.2021
Fin & Admin Business Associate
IBM
05.2018 - 01.2019
Master of Science - Data Science
Liverpool John Moores University
04.2001 - 04.2021
Bachelor of Technology - Computer Science
Guru Gobind Singh Indraprastha University
04.2001 - 04.2017
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