Experience

Gradient AI

• United States
• Software Development
• 1 - 100 Employee

• Staff Data Scientist

  • ago. de 2022 - - actualidad



Acousense

• New York, United States

• Founder

  • jul. de 2021 - - actualidad

  Founder & Principal Data Scientist at Acousense, we are a digital machine health company providing solutions to monitor industrial assets and keep them in good working condition. Founder & Principal Data Scientist at Acousense, we are a digital machine health company providing solutions to monitor industrial assets and keep them in good working condition.



SymphonyAI Sensa-NetReveal

• United States
• Software Development
• 100 - 200 Employee

• Head of Data Science US

  • sept. de 2020 - jun. de 2021

• Sr. Data Scientist

  • nov. de 2016 - ago. de 2020

  Develop software to process large volumes of Data and build predictive models. Utilize advanced mathematical concepts in Topological Data Analysis to gather insights from Data, build supervised, unsupervised and anomaly models and deploy them in production. Some of my recent work includes:1. Build and deploy customer segmentation models using topological data analysis for Anti-money laundering (AML). The models are deployed in production and part of the AML processes at one of the world's largest banks2. Developed portfolio credit risk models by analyzing financial information of companies (which includes annual and quarterly reports, stock price, bond prices, macro-economic data) to identify companies in risk of credit downgrades 6 months ahead of time3. Developed models to detect mortgage fraud for the largest US mortgage securitizer4. Developed models for customer product recommendations to a large grocery chain5. Developed customer churn models to the largest telecom network provider in India Mostrar menos



Feedzai

• United States
• Information Technology & Services
• 400 - 500 Employee

• Data Scientist

  • jun. de 2015 - nov. de 2016

  Developed predictive models to detect fraud in credit/debit card transactions. The developed models were deployed in production at one of the worlds largest card transaction network provider. Utilized an approach of offline model building and online predictive scoring of risk for transactions. The model and systems deployed provide risk score to a live transaction based on usage history, ongoing transactions in real time. Developed predictive models to detect fraud in credit/debit card transactions. The developed models were deployed in production at one of the worlds largest card transaction network provider. Utilized an approach of offline model building and online predictive scoring of risk for transactions. The model and systems deployed provide risk score to a live transaction based on usage history, ongoing transactions in real time.



MISTRAS Group, Inc.

• United States
• Specialty Trade Contractors
• 700 & Above Employee

• Research Scientist

  • ago. de 2010 - jun. de 2015

  Responsible for research and development of Structural Health Monitoring (SHM) systems to monitor critical infrastructure like Bridges, Turbines (Combustion, Wind Turbines), Storage Tanks etc. Developed ultrasonic and acoustic emission sensors, sensor deployment strategies on large structures, data acquisition, signal processing solutions. Analyzed huge volumes of data collected on these structures to determine the probabilistic damage locations on the structures. Utilized Pattern Recognition/Machine Learning Techniques to build autonomous systems that can analyze the real time sensor data generated on these structures. Mostrar menos



Penn State University

• United States
• Higher Education
• 700 & Above Employee

• Research Assistant

  • ago. de 2005 - ago. de 2010

  My research involved the development of ultrasonic guided wave based non destructive testing techniques for permanent Structural Health Monitoring (SHM) of structures like composite plates, tanks and pipes. My studies are focused on developing theoretical models and experimentally verifying the solutions on structures. I developed Pattern Recognition/Machine Learning techniques for developing prognostic models for the structures from the sensor data acquired. My research involved the development of ultrasonic guided wave based non destructive testing techniques for permanent Structural Health Monitoring (SHM) of structures like composite plates, tanks and pipes. My studies are focused on developing theoretical models and experimentally verifying the solutions on structures. I developed Pattern Recognition/Machine Learning techniques for developing prognostic models for the structures from the sensor data acquired.