Anjila S
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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 Response Time 12.0 hours
- Average Count of Messages/Day 0.4
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 14h PST, 28h 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 3.0/5
- Technical Breadth 3.0/5
- Algorithmic Thinking 4.0/5
- Technical Strength 4.0/5
- Teamwork 3.0/5
- Intellectual Merit 3.0/5
- English Communication 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: 14h 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
04 - 08
04 - 08
04 - 08
04 - 08
04 - 08
04 - 08
04 - 08
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
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