Merishna 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
$31.25 /hr $ 50.0K /yr Hourly Rate and Yearly Salary
Overview
Basic Summary
LD Talent History - Worksession Approval 100.0%
- Average Response Time 7.0 hours
- Average Count of Messages/Day 1.2
- Project Completion Rate 2/4
- Interview Acceptance Rate 4/6
- Timezone Overlap 6h PST, 48h UTC
- No. of Passion Projects 3
- Earned Hours 35.50
- 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
- Desktop Windows
- Phone Android
- Member Since Jun 04, 2020
- Profile Last Updated Jul 07, 2022
- Last Activity June 28, 2023, 4:02 p.m. UTC
- Location Nepal
Profile Summary
Artificial intelligence & machine learning engineer with strong fundamentals in machine learning algorithms (neural networks, dimensionality reduction, feature utilization, and extraction and clustering), programming, statistics, and mathematics. Experience in development and implementation of systems and machine-learning concepts. Love working with data including gathering the data, understanding it, cleaning, normalizing, and extracting in a usable format.
Skills
Total Experience: 7 years
Python (10E, 7Y, 1C)
10 experiences, across 7 years, with 1 courseMachine learning (4E, 7Y, 2C)
4 experiences, across 7 years, with 2 coursesscikit-learn (6Y)
6 years of experienceFirebase (6Y)
6 years of experienceTensorflow (2E, 6Y)
2 experiences, across 6 yearsDocker (3E, 4Y)
3 experiences, across 4 yearsData Analytics (2E, 3Y, 1C)
2 experiences, across 3 years, with 1 courseAWS (2E, 3Y)
2 experiences, across 3 yearsMatplotlib (2Y)
2 years of experiencePandas (2Y)
2 years of experiencePlotly (2Y)
2 years of experienceNatural language processing (2Y)
2 years of experienceComputer vision (2E, 2Y)
2 experiences, across 2 yearsMongoDB (2Y)
2 years of experienceGoogle Cloud
Deep learning (3E, 2Y, 1C)
3 experiences, across 2 years, with 1 coursekeras (2E, 2Y)
2 experiences, across 2 yearsGoogle Computer Vision API (2Y)
2 years of experienceOCR (2Y)
2 years of experienceSQL (1C)
1 courseData visualization (1C)
1 courseProbabilistic graphical models (1C)
1 courseArtificial intelligence (1C)
1 course
Weekly Availability
Timezone Overlap with 06 - 21 per Week: 6h PST, 48h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
UTC
07 - 15
07 - 15
07 - 15
07 - 15
07 - 15
07 - 15
PST
23 - 07
23 - 07
23 - 07
23 - 07
23 - 07
23 - 07
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
Data Scientist/CTO
Employment
Feb 2019 - Present
Kharpann Enterprises Pvt. Ltd. Company
Technology Industry
Project: Data Science and AI
- The lead programmer for building data analytical processes for different spatial as well as non-spatial data related projects using Tensorflow, scikit-learn and Machine learning algorithms.
- Building and improving intelligent machine learning models for data science solutions using Python and NoSQL databases such as Firebase, MongoDB.
- Analyze data and generate insights and pipelines to automate business processes.
- Involved in initiating research and development related to tech stacks and strategies for scaling based on the road map of the company.
Data Scientist
Employment
May 2021 - Mar 2022
Doorstead Inc. Company
Real Estate Industry
Project: Data Science
- Development of internal dashboards for monitoring KPIs, calibrating model metrics, and predictions using Python, Streamlit, Apache Airflow and MLFlow.
- Performed Data Analytics and outlier detection to generate monthly reports for improving marketing emails using Pandas, Matplotlib, Plotly, Docker and AWS.
Data Scientist
Employment
Sep 2018 - Feb 2019
Docsumo Company
Technology Industry
Project: Document Parser
- Built the preprocessing pipeline for Data Extraction of scanned and pdf documents using Python, Computer Vision and Image Processing.
- Configured the Optical Character Recognition for scanned and pdf documents using Tesseract and Google Vision API.
- Conducted extensive research on creating and improving the parameter for Natural language processing and Image segmentation using Convolutional Neural Network model for documents.
- Deployed the document classification tool as a web app using Docker and Flask.
- Developed the database structure and storing pipeline for MongoDB and created the testing and caching mechanism of database requests for web app using MongoDB and Redis Queue.
Developer
Passion Project
Dec 2018 - Jan 2019
Company
Technology Industry
Project: Cheque Parser
- Developed a OCR and parsing project for Bank Cheques.
- The project takes in scanned or unscanned image of a Bank cheque, preprocesses it using Computer Vision and Image processing techniques.
- The OCR is done with the help of Python, Tesseract and Google Computer Vision API.
- Machine learning alogirthms are used to classify different areas of the image to detect Name, Account Number and other details.
Data Science
Internship
Jun 2018 - Sep 2018
Arch Analytics Company
Technology Industry
Project: Data Science and AI
- Worked on major data science and AI projects involving Python Data Analytics. Responsible for conducting extensive preliminary research for feasibility and analysis of Deep Learning projects.
- Involved in idea formation and R&D for data parser SaaS product using Computer Vision, Natural Language Processing, and Google Cloud Services.
- Worked on research and model development for multi-label classification of HS codes using Keras and AWS Sagemaker.
- Conducted research and developed a model for time-series analysis and prediction of Freight rates using Scrapy, ARIMA, FbProphet, Docker.
Developer
Passion Project
Aug 2018 - Sep 2018
Company
Technology Industry
Project: Recommendation Engine
- Built a recommendation engine for recommending books based on user preferences.
- The engine was created using Python, turicreate and uses Machine learning algorithm for Collaborative filtering.
- The system works on the assumption that people like things similar to other things they like, and things that are liked by other people with similar taste.
LD Experience
Client Projects
Blog Projects
How to create a Deep Learning face mask classifier for COVID-19 in public spaces
May 2022 - Jun 2022
Developer
- Developed a Deep Learning classifier in Python for detecting mask in people's faces in public.
- Used keras library for building the VGG-net architecture of Convolutional Neural Network (CNN).
How to diagnose hypothyroid disease using Deep Learning
Oct 2020 - Nov 2020
Developer
Arts and Entertainment Industry
- Used Deep Neural Networks in Deep Learning to perform diagnosis of hypothyroid disease in Python.
- Used Keras for building the Deep Neural Network in Python.
How to generate unique architectures using GANs
Oct 2020 - Oct 2020
Developer
Technology Industry
- Used Generative Adversarial Networks (GANs) in Deep Learning to train and generate architectural images in Python.
- Used TensorFlow for creating the deep neural network for GAN model.
Coding Challenges
Skill:
- Python
- Machine learning
- scikit-learn
- Firebase
- Tensorflow
- Docker
- Data Analytics
Basic
Sep 2020 - Jan 2022
Basic
Sep 2020 - Jan 2022
Basic
Sep 2020 - Jan 2022
Video Projects
How to implement django-tenant-schemas with a fixed URL
Sep 2020 - Jan 2022
Frontend Developer
Technology
- Python
- Machine learning
- scikit-learn
- Firebase
- Tensorflow
- Docker
- Data Analytics
- Led user research for a new construction site documentation tool.
- Hosted workshops to synthesize user insights into design requirements.
- Designed 3D concepts and built prototypes to investigate new tool form factors.
- Researched existing digital solutions and prioritized key features for app release.
LD Ventures
Thea
Sep 2020 - Jan 2022
Frontend Developer
Technology
- Python
- Machine learning
- scikit-learn
- Firebase
- Tensorflow
- Docker
- Data Analytics
- I used the Django Rest Framework to create a multi tenant API with the aid of the django-tenant-schemas package.
- I used the Postgres Database as the persistence layer and specifically the PostgreSQL Schemas to ensure that all tenants using the API had their data.
- I used the REST architecture in designing my API.
- Researched existing digital solutions and prioritized key features for app release.
Qualifications
Education
Kathmandu Engineering College
Sep 2015 - May 2019
B.E. (Computer Engineering)
Courses