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Rahul T - Python developerLD Talent logo

Rahul T

The star rating is calculated by averaging the reviews provided by all clients the talent has worked with for a significant amount of time.

If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.

If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.

Other data including reviews from interviews are available on the talents’ profiles but do not influence their star rating, though they do influence their position in the search results.
SOFTWARE ENGINEER Preferred Title
$43.75 /hr $ 80.0K /yr Hourly Rate and Yearly Salary
Overview Vetting Experiences Qualifications
Overview
Basic Summary
LD Talent History
  • Average Response Time 12.0 hours
  • Average Count of Messages/Day 0.4
  • Project Completion Rate 2/4
  • Interview Acceptance Rate 4/6
  • Timezone Overlap 43h PST, 31h UTC
Vetting Summary
  • Code Quality 60%
  • Soft Skill Attributes 60%
  • Expertise 2/3
  • Coding Challenges 60%
  • No. of Lifelong Learning Projects 2
  • No. of Coding Challenges Completed 2
  • More details
Interview Scores (4.7/5)
  • Software Engineering Process 4.0/5
  • Technical Breadth 4.0/5
  • Algorithmic Thinking 5.0/5
  • Technical Strength 5.0/5
  • Teamwork 5.0/5
  • Intellectual Merit 5.0/5
Talent's Devices
  • Desktop Windows
  • Phone Android
General
  • Member Since Oct 26, 2020
  • Profile Last Updated Jun 17, 2021
  • Last Activity June 17, 2021, 1:45 p.m. UTC
  • Location United States of America
  • Current Status Student
Profile Summary
I am enthusiastic about growing as a data scientist and software developer. I have experience working as an Application Developer as well as Machine Learning researcher.
Skills
Total Experience: 5+ years
  • Python (5E, 4Y)

    5 experiences, across 4 years
  • Machine learning (2E, 3Y)

    2 experiences, across 3 years
  • Git (1E, 3Y)

    1 experience, across 3 years
  • Jupyter (1E, 1Y)

    1 experience, 1 year
  • Data visualization (1E, 1Y)

    1 experience, 1 year
  • Data Science (1E, 1Y)

    1 experience, 1 year
  • Data Analytics (1E, 1Y)

    1 experience, 1 year
  • Deep learning (2E, 1Y)

    2 experiences, 1 year
  • Tensorflow (2E, 1Y)

    2 experiences, 1 year
  • Nodejs (1E, < 1Y)

    1 experience, less than a year
  • MongoDB (1E, < 1Y)

    1 experience, less than a year
  • AWS S3 (1E, < 1Y)

    1 experience, less than a year
  • AWS EC2 (1E, < 1Y)

    1 experience, less than a year
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 43h PST, 31h UTC
Day
Sunday
Monday
Wednesday
Friday
Saturday
UTC
13 - 24
13 - 17
18 - 24
13 - 24
13 - 24
PST
06 - 17
06 - 10
11 - 17
06 - 17
06 - 17
Vetting
  • Interview Data
  • Agile Development Process
  • Productivity and Responsiveness
  • Teamwork
  • Software Engineering
  • Logical Thinking
  • Technical Strength
  • Intellectual Merit
  • English Communication
  • Documentation
  • System Design
  • Coding Challenges
    60%
  • Algorithms Score
    60%
  • General Score
    60%
  • Easy Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Medium Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Hard Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Expertise
    2/3
  • Design Patterns and Architectures
    2/3
  • Debugging
    2/3
  • Stack Traces
    2/3
  • Testing
    2/3
  • System Administration
    2/3
  • Soft Skill Attributes
    60%
  • Entrepreneurial
    60%
  • Whole Brained
    60%
  • Divergent Thinking / Creativity
    60%
  • Design Ability
    60%
  • Empathy
    60%
  • Project Management Ability
    60%
  • Security
    60%
  • Code Quality
    60%
  • Complex Logic
    60%
  • Models
    60%
  • Controllers
    60%
  • Templates
    60%
  • APIs
    60%
  • Training/Testing Data Models
    60%
  • Code Readability
    60%
  • Ongoing Evaluation
  • Number of Lifelong Learning Project
    2
  • Number of Coding Challenge Completed
    3
  • Lifelong Learning Project 1
  • Lifelong Learning Project 1
  • Coding Challenges 1
  • Coding Challenges 2
  • Coding Challenges 3
Experience
Student
Contract
Jan 2020 - Present
Villanova University Company
Research Industry
Project: Differential Testing in Hyperdimensional Computing
  • Git
  • Python
  • Machine learning
  • Minimized energy consumption on image processing applications by ~80% under a quality constraint of 0-5% by finding an optimal combination of approximate settings using genetic algorithm on Python.
  • Designed algorithm to perform differential testing on Hyperdimensional computing, a new Machine Learning paradigm, for image processing application.
  • Used Git and GitHub for storing all the project files.
Student
Course Project
May 2020 - Aug 2020
Villanova University Company
Research Industry
Project: COVID-Net
  • Tensorflow
  • Python
  • Deep learning
  • Designed a small-sized neural network (Deep Learning) using SqueezeNet and CapsNet to diagnose COVID-19 from chest X-ray.
  • Preprocessed and augmented X-ray data, and trained model on Tensorflow using Python, achieving an accuracy of 95.0%.
Software Engineer
Internship
May 2020 - Jul 2020
The Vanguard Group Company
Finance Industry
Project: Data Validation and Optimization
  • AWS S3
  • MongoDB
  • Nodejs
  • AWS EC2
  • Python
  • Validated on-prem fund data against the cloud data using Python for the analytics team to address any discrepancies.
  • Refactored and deployed Gurobi optimization models by connecting it with AWS (AWS EC2 and AWS S3) using Boto3.
  • Created REST APIs using Flask to extract the analytics data from an on-prem server and store them in AWS.
  • Developed intramural sports league web app using Angular, Nodejs, and Mongodb in collaboration with 8 interns.
Developer
Internship
Jun 2019 - Aug 2019
University of California Irvine Company
Research Industry
Project: Modeling Signal Delay in UAV systems
  • Deep learning
  • Tensorflow
  • Python
  • Machine learning
  • Designed a mutual information-based algorithm (Machine Learning) to select 10/100 best features in an unmanned aerial vehicle system.
  • Modeled a Recurrent Neural Network (Deep Learning) in Tensorflow using Python to predict signal delay using sequence-to-sequence based approach with an accuracy of ~80% for a highly skewed dataset.
Student
Internship
Jan 2018 - Aug 2018
Villanova Physics Department Company
Research Industry
Project: Image Modeling and Data Analytics
  • Data Analytics
  • Data Science
  • Jupyter
  • Data visualization
  • Python
  • Created histogram of relative orientation between the magnetic field and the intensity gradient using data visualization library such as seaborn and matplotlib in Python/Jupyter Notebook.
  • Modeled a Red Blue Green image of Orion Nebula and plotted magnetic vectors over the image using Pandas and APLpy, a data science/data analytics library
Github Links
  • https://github.com/ThapaRahul/RGB_Image_Modeing_SummerResearch2018
Qualifications
Education
Villanova University
Aug 2017 - May 2021
BS (Computer Science)
Courses
Deep Learning
Jan 2020 - May 2020
Villanova University
  • Deep learning
  • Python
  • Machine learning
Platform Based Computing
Aug 2019 - Dec 2019
Villanova University
  • React
  • Nodejs
  • Git
  • PHP
Software Engineering
Jan 2020 - May 2020
Villanova University
  • Python
  • Java
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