RohanYashraj / RohanYashraj_archive

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Hi there, I'm Rohan!

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I am a creative🎡, time punctual👩‍🎓, dedicated🎯, goal-oriented individual👩‍💻 with decent moral Values and Ethicates🙇‍♀️ along with a high-energy level🤹‍♀️, honed communication skills👐, strong organizational skills👮‍♀️, and meticulous attention🕵️‍♀️ to detail.


Click here to visit my Portfolio -> https://rohanyashraj.github.io


👨‍💻 Actuarial Data Science Implementations

  • Fraud Detection Tool (Part of PhD work) Click Here

    • Built a tool on RShiny to detect motor insurance fraud
    • Tools used : R  RShiny  HTML  Heroku  Flask  Markdown  Git 
  • Ayushman Bharat Claims Analytics

    • Provided claims analytics to the broker and insurance company
    • Built Shiny app dashboard on R for users to track the claims experience on a monthly basis
    • Analysed claim patterns and fraud during COVID period
    • Tools used : R  RShiny  HTML 
  • Crop Insurance Pricing

    • Web scraping of daily yield data for various crops using python
    • Projecting crop yield data using ARIMA model
    • Built a dashboard to track futures value under different scenarios for various crops
    • Tools used: R  RShiny  Excel  Python  Pandas  NumPy  Selenium 
  • Cancer Product Pricing

    • Helped price cancer product for various types of cancer across different states in India
    • Built a dashboard for easy comparison and visualization of frequency, severity and risk premiums by gender and state
    • Tools used: R  RShiny  Python  Excel 
  • Gratuity valuation

    • Developed an Excel spreadsheet that eased gratuity valuation as an actuarial consulting assignments
    • Tools used: Excel 
  • Learning Management System for the University

    • Built, customized and implemented the Learning Management System for the university
    • Tools used : AWS  HTML 

👨‍💻 Work Experience (Data Science Specific)

  • CAS Student Central Independent Summer Internship Program | Jun 2020 – Aug 2020
    Casualty Actuarial Society – USA

    • Participated in a program spanning 6 weeks focused on various aspects of Property & Casualty
    • Attended practical webinars by Qualified Actuaries, and completed projects designed by them
    • Attained insights into data visualization, pricing, reserving and predictive modelling
  • Learning Management System for University | Apr 2020 – Jul 2020

    • Part of the core team which built, customized and implemented the Learning Management System for the university (SSSIHL)
    • Helped deploy the system through Amazon Web Services to facilitate the access of the system by all the students and faculty members using their laptops or mobile phone anywhere in the world
    • Around 1400 users use this on a daily basis
  • Doctor of Philosophy, Actuarial Science | Jun 2019 – Present
    Sri Sathya Sai Institute of Higher Learning

    • Developing a novel approach to data-driven fraud detection and prevention in insurance using actuarial and data science techniques
    • Building a proof of concept fraud detection tool which can be accessed via web by the user
  • Department of Mathematics and Computer Science | Jun 2019 – Present
    Sri Sathya Sai Institute of Higher Learning

    • Teaching Actuarial Science subjects for Masters
    • Providing Actuarial Dissertation Research support
  • Workshop Hands-on Predictive Analytics with Python | Feb 2021 – Mar 2021
    Sri Sathya Sai Institute of Higher Learning

    • Part of a team that conducted a 5 week long workshop on hands-on predictive analytics using python
    • With Jupyter Notebook as a platform for python implementation, demonstrated the use of packages like numpy, pandas, matplotlib and scikit learn
    • Provided hands-on training on various Machine Learning and Deep Learning models
  • Conference Presentations

    • “A proposed unsupervised learning approach for fraud detection in automobile insurance using Apache Spark” in International Virtual Conference on Distributed Computing, Intelligence & it's Applications IVCDCIA, 2020.
    • “Implementation of a Predictive Model for Fraud Detection in Motor Insurance using Gradient Boosting Method and Validation with Actuarial Models,” in 2019 IEEE International Conference.

📜 Actuarial Exams

  • Institute and Faculty of Actuaries (IFoA) – UK | Sep 2017 – Present

    • CS1, CS2, CM1, CM2, CB1, CB2, CB3, CP1, CP2, CP3
  • Society od Actuaries (SOA) – USA

    • Exam PA, FAP Module, VEEs

✍ Actuarial Membership

I am a member of two Actuarial bodies:

  • Institute of Faculty and Actuaries (IFoA) | UK | 2017 to present | Associate Member
  • Society of Actuaries (CAS) | USA | 2019 to present | Associate Member

📜 Research Publications

  • A Comparative Study of Using Various Machine Learning and Deep Learning-Based Fraud Detection Models For Universal Health Coverage Schemes. Click Here
  • TGANs with Machine Learning Models in Automobile Insurance Fraud Detection and Comparative Study with Other Data Imbalance Techniques. Click Here
  • “A proposed unsupervised learning approach for fraud detection in automobile insurance using Apache Spark,” in International Virtual Conference on Distributed Computing, Intelligence & it’s Applications IVCDCIA, 2020.
  • A Proposed Model for Measuring Protection of Policyholders’ Interest at Industry Level, IRDAI Journal. Click Here
  • Implementation of Correlation and Regression Models for Health Insurance Fraud in Covid-19 Environment using Actuarial and Data Science Techniques. Click Here
  • Implementation of a Predictive Model for Fraud Detection in Motor Insurance using Gradient Boosting Method and Validation with Actuarial Models. Click Here
  • A Framework for Comprehensive Fraud Management using Actuarial Techniques. Click Here

🤷‍♂️ Talking about personal stuff

  • 🔭 I’m currently working on "Building a data-driven fraud detection and prevention tools for insurance business using Actuarial and Data Science tools"
  • 🌱 I’m currently learning Flask, R-Shiny, AWS
  • 🤔 I’m looking for help with Rule-engine and cloud platform
  • 💬 Ask me about anything - I am happy to help!
  • 📫 How to reach me: rohanyashraj@gmail.com

🔧 Technologies I've been learning and using so far

  • Programming languages :
    Python  R  RShiny  C 

  • Machine Learning / Deep Learning frameworks :
    TensorFlow  Scikit-learn  Keras 

  • Frontend :
    HTML  CSS  Jinja  WordPress 

  • Backend :
    AWS  Heroku  Flask 

  • OS & IDE :
    Jupyter  RStudio  PyCharm  Markdown  Ubuntu  Windows 

  • Tools :
    Excel  Office  Powerpoint  Git  GitHub  Anaconda  OBS 

  • Packages :
    Pandas  NumPy  Selenium 

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