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Data Scientist
Location New Delhi
Total Views51
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Member since30+ Days ago
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Candidate Information
  • User Experience
    Experience 0.3 Year
  • Cost
    Hourly Rate$3
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    Work FromAny
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    CategoryInformation Technology & Services
  • back in time
    Last Active OnJune 02, 2024
Key Skills
DevopsMySQLMachine LearningSupply Chain ManagementTableauPython

RESEARCH PROJECTS Pandemic Forecasting | CDAC | Government of India (2020)

• Forecasted the course of the pandemic using timeseries data of incoming cases to help the government devise control measures

• Performed feature engineering by adding stages and inflection points based on Gaussian Mixture Models and Markov Chain Models

• Used Poisson Regression on top of SIRD baseline to predict the incoming cases, number of deaths and achieved R2 score of 0.96 & 0.99 Assessing Supply Chains in era of Industry 4.0 using Attack Graphs | INFORMS Conference, USA (2019)

• Analysed expected time for network disruption pertaining to modular exploitation of vulnerabilities for cyber-physical supply chains

• Defined exploitability of the nodes considering inherent risks and external risks and modelled the system using Attack Graphs

• Simulated the model to study the effect of systemic risks and found that ~90% of the time flow of goods disrupt due to resource crunch Fraud Detection Modelling in Credit Card Transactions | IIT Kharagpur (2018)

• Performed a comparative evaluation of classifiers for near-real time detection of fraudulent credit card transactions

• Applied SMOTE to handle the class imbalance and used Stratified Shuffle split during cross validation to preserve class proportion

• Achieved accuracy of 97.4% on the test dataset and 99.9% on training dataset using XgBoost technique among boosting techniques. Survival Analysis of Supply Chain using Probit Stick Breaking Process | 5th ICBAI Conference, IIM Bangalore (2017)

• Investigated ways to assess and forecast production line failure risk and designed a predictive maintenance schedule for the equipment

• Developed a novel ‘Bayesian Nonparametric Mixture Model’ to determine posterior predictive density of time-to-failure of machines

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