Lakshya Gupta
Summary
Accomplished Lead Data Analyst with 7 years of experience in developing scalable data-driven solutions from structured and unstructured data sources. Demonstrated expertise in predictive data models and algorithms, specializing in multivariate analysis and extracting valuable insights from complex datasets. Currently leading a team of Data Scientists/Analysts working, planning and analyzing marketing campaign, building machine learning models, challenger models for model validation, and forecast analysis
Overview
9
9
years of professional experience
Work History
Lead Data Analyst(Senior Manager)
EXL Service
09.2021 - Current
- Currently leading a team of data scientists/analysts focused on building machine learning models, challenger models for model validation, marketing campaign analysis and forecast analysis
- Collaborated on the development of models and triggers for multiple acquisition and loyalty campaigns for a credit card company
- Additionally, designed and implemented an automated framework for evaluating campaign performance, which empowered the Marketing team to make data-driven decisions
- Developed a predictive credit risk model for a Consumer Lending Firm by leveraging bank statement data in conjunction with existing credit bureau data. The model utilized Gradient Boosting as the base algorithm, resulting in an increase in the AUC of the underwriting model from 0.67 to 0.74
- Conducted validation of 8 credit risk models for various clients and use cases in Consumer/Small Business Lending
- This involved building challenger models and assessing conceptual soundness, model performance, governance, and providing enhancement recommendations to clients
Senior Tech Data Analyst
Bank of New York Mellon Technologies
06.2016 - 07.2019
- Responsible for designing end-to-end pipelining of predictive models from data extraction, feature engineering, data visualization in tableau to model retraining
- Developed a predictive model (Catboost classifier) in Python to predict trade failure with the probability of failure and reduced manual efforts from 18 percent to 6 percent
- Deployed these predictive models to the company's cloud platform and leveraged Flask to develop REST APIs to allow the line of business to access these models
- Involved in enhancing accuracy, improving training time, feature engineering enhancements, and scalability of the currently deployed fraud detection model (Neural Net in H2o) of the bank
- Leveraged Stanford core-NLP to semantically extract entities (rates, currencies, basis points, and duration) from unstructured data in fee schedules pdfs using NER (Named Entity Recognition), POS, and dcoref annotators for a project Revenue Leakage Audit platform
- Created a User Interface for this project using Java Swing to reconcile billing discrepancies in fee components configured in the billing system
Research Assistant
Science of Science and Computational Discovery Lab, Syracuse University
02.2020 - 04.2020
- Built a computer vision model to detect misleading graphs in research papers for predicting future academic success by removing the potential biases helping scientists and funding agencies to commit during peer review
- Utilized Darknet Yolo v3 algorithm and OpenCV, training a graph detector model to classify the various graphs
Education
MS - Applied Data Science
Syracuse University
Syracuse, NY05.2021
B.Tech - Chemical Science and Technology
Indian Institute of Technology
05.2016
Skills
- Technologies: Machine Learning, NLP, Computer Vision, Big Data(HIVE, HADOOP)
- Programming Languages: Python, R, SQL, BigQuery
- Analytical Tools: Power BI, Tableau, Microsoft Excel, Open Refine
- Cloud and DevOps Tools: AWS, Docker, Git, Google Cloud Platform (GCP), JIRA, Kubernetes, Microsoft Azure
Timeline
Lead Data Analyst(Senior Manager)
EXL Service
09.2021 - Current
Research Assistant
Science of Science and Computational Discovery Lab, Syracuse University
02.2020 - 04.2020
Senior Tech Data Analyst
Bank of New York Mellon Technologies
06.2016 - 07.2019
B.Tech - Chemical Science and Technology
Indian Institute of Technology
MS - Applied Data Science
Syracuse University
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