Rahul T
The star rating is a representation of the overall rating, calculated as the mean of the client satisfaction rating, the average client interview rating, and internal interview scores.
The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.
If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
The client satisfaction rating is the weighted average of client ratings, with weights based on reviewed work hours. When no client rating exists, the approval fraction (approved vs. reviewed work hours) determines it.
If the client satisfaction rating exceeds the overall rating, it becomes the star rating. In the absence of client ratings, if the average client interview rating is higher than the overall rating, it becomes the star rating. If no data is available, the star rating defaults to the internal interview score.
SOFTWARE ENGINEER Preferred Title
$43.75 /hr $ 80.0K /yr Hourly Rate and Yearly Salary
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 39h PST, 31h UTC
- 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
- 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
- Desktop Windows
- Phone Android
- 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: 7 years
Python (5E, 7Y, 2C)
5 experiences, across 7 years, with 2 coursesMachine learning (2E, 6Y, 1C)
2 experiences, across 6 years, with 1 courseGit (5Y, 1C)
5 years of experience, with 1 courseJupyter
Data visualization
Data Science
Data Analytics
Deep learning (2E, 2Y, 1C)
2 experiences, across 2 years, with 1 courseTensorflow (2E, 2Y)
2 experiences, across 2 yearsNodejs (1C)
1 courseMongoDB
AWS S3
AWS EC2
React (1C)
1 coursePHP (1C)
1 courseJava (1C)
1 course
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 39h PST, 31h UTC
Day
Sunday
Monday
Wednesday
Friday
Saturday
UTC
13 - 24
13 - 17
18 - 24
13 - 24
13 - 24
PST
05 - 16
05 - 09
10 - 16
05 - 16
05 - 16
Vetting
- Interview Data
- Agile Development Process
- Productivity and Responsiveness
- Teamwork
- Software Engineering
- Logical Thinking
- Technical Strength
- Intellectual Merit
- English Communication
- Documentation
- System Design
- Coding Challenges60%
- Algorithms Score60%
- General Score60%
- Easy Algorithm
- Correctness60%
- Performance60%
- Medium Algorithm
- Correctness60%
- Performance60%
- Hard Algorithm
- Correctness60%
- Performance60%
- Expertise2/3
- Design Patterns and Architectures2/3
- Debugging2/3
- Stack Traces2/3
- Testing2/3
- System Administration2/3
- Soft Skill Attributes60%
- Entrepreneurial60%
- Whole Brained60%
- Divergent Thinking / Creativity60%
- Design Ability60%
- Empathy60%
- Project Management Ability60%
- Security60%
- Code Quality60%
- Complex Logic60%
- Models60%
- Controllers60%
- Templates60%
- APIs60%
- Training/Testing Data Models60%
- Code Readability60%
- Ongoing Evaluation
- Number of Lifelong Learning Project2
- Number of Coding Challenge Completed3
Experience
Student
Contract
Jan 2020 - Present
Villanova University Company
Research Industry
Project: Differential Testing in Hyperdimensional Computing
- 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
- 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
- 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
- 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
- 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
Qualifications
Education
Villanova University
Aug 2017 - May 2021
BS (Computer Science)
Courses