
Anjila S
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.
Data Scientist Preferred Title
$19.00 /hr $ 17.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Average Count of Messages/Day 0.4
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 21h PST, 28h UTC
- No. of Onboarding MCQs Completed 6 More details
- Software Engineering Process 3.0/5
- Design Practice 3.0/5
- Design Theory 3.0/5
- Technical Breadth 3.0/5
- Logical Thinking 4.0/5
- Technical Strength 4.0/5
- System Design 3.0/5
- Productivity and Responsiveness 3.0/5
- Teamwork 3.0/5
- Agile Development Process 3.0/5
- Intellectual Merit 3.0/5
- English Communication 3.0/5
- Documentation 3.0/5
- Desktop Windows
- Phone iPhone
- Member Since Mar 17, 2024
- Profile Last Updated Jun 17, 2024
- Last Activity June 17, 2024, 8:41 a.m. UTC
- Location Nepal
- Current Status Student
Profile Summary
I am currently a third-year Btech in AI student here at Kathmandu University, Nepal. I am very enthusiastic about Data Science and Machine Learning. I have also collaborated in Omdena Local Chapters and Innovation challenges to hone my skills. With AI/ML I know backend Django RestFrameWork and Frontend basics HTML/CSS/JS.
Skills
Total Experience: 1+ years
Django (2E, 2Y)
2 experiences, across 2 yearsConvolutional Neural Networks (2Y)
2 years of experiencePython (2Y, 1C)
2 years of experience, with 1 courseGraphs And Networks (2Y)
2 years of experienceNatural language processing (2Y)
2 years of experienceLSTM (2Y)
2 years of experienceBERT (2Y, 1C)
2 years of experience, with 1 courseTransformer (2Y, 1C)
2 years of experience, with 1 courseDeep Learning (Theory) (1C)
1 courseNeural Networks (1C)
1 course
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 21h PST, 28h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
12 - 16
12 - 16
12 - 16
12 - 16
12 - 16
12 - 16
12 - 16
PST
05 - 09
05 - 09
05 - 09
05 - 09
05 - 09
05 - 09
05 - 09
Vetting
- Interview Data
- Software Engineering Process
- Design Practice
- Design Theory
- Technical Breadth
- Logical Thinking
- Technical Strength
- System Design
- Productivity and Responsiveness
- Teamwork
- Agile Development Process
- Intellectual Merit
- English Communication
- Documentation
Experience
Machine Learning Engineer
Course Project
Apr 2023 - Apr 2024
Kathmandu University Company
Technology Industry
Project: Sheild Talk
- Sheild Talk was a full-stack web project with Django as the backend. We used NLP to make our network from the very scratch and learned how to make Natural language processing networks.
- We used Bidirectional LSTMs for toxicity classification because they capture the context and dependencies in text data, which can be difficult to model with other models.
- We then upgraded our model with a Transformer i.e. BERT, We finetuned the model and deployed the model into the streamlit. I learned how to integrate and finetuned the transformer according to need.
Machine Learning Engineer
Passion Project
Feb 2023 - Mar 2024
Shequal Foundation Company
Technology Industry
Project: SignBloom
- SignBloom was a full-stack project with Frontend and Backend integrated. It Started as a hackathon Project where we were able to integrate the AI/ML with the Django(Python) backend.
- I was able to make a Convolutional Neural Networks model that could correctly classify up to 10 sign language letters/ as in images and use that to predict the sign in real-time.
- To Upgrade this project, We took this as and Semester project and used GAT(Graphs and Networks) i.e Graph Attention Network to capture similar patterns while training the collected images.
Qualifications
Education
Kathmandu University
Feb 2021 - Dec 2025
B.tech (Artificial Intelligence)
Courses
DeepLearning.AI
Google Cloud Training