Data Analytics
Data Visualization
Machine Learning
Deep Learning
About the company
Our Story
Kharpann was founded in 2019 by three data enthusiasts working from a godown office and today, it is a year-old data science company with its services spanning across multiple industries. You’ll find that our small but neatly picked team has years of experience working as mathematicians, programmers and artificial intelligence/machine learning engineers.
The company’s name, ‘Kharpann’, has its root stemming from the ancient Kathmandu Valley of Nepal. The word symbolizes a two-sided vending basket balanced on a bamboo trunk and this arrangement resonates with our core principle: always balance the charm of data science with its actual value.
Also, we can't help but mention that our flagship product has always been our own team.
Meet the team
Get to know the people behind Kharpann.
Merishna S. Suwal
Data ScientistMerishna has a professional data science background displaying expertise in Computer Vision and Natural Language Processing. She was formerly part of the data science team at Docsumo and she is cherished for architecting, building and deploying complex deep learning models into production.
Pragyan Subedi
Data ScientistPragyan is listed on Toptal as one of the top 3% freelancing data scientists in the world. He was formerly part of the data science teams of companies such as F1Soft International and Tootle and he is cherished for evangelising in-house and off-shore business processes through the use of data.
Suyog Dahal
Data ScientistSuyog is a competitive Kaggler and holds years of experience in performing exploratory data analysis of large datasets. He is also the current vice president of the Kathmandu Engineering College IT Club and he is cherished for his expertise in descriptive, prescriptive and predictive analytics.
We are mathematicians
Linear Algebra
Calculus
Probability
Statistics
We are programmers
Python
TensorFlow
PyTorch
Scikit-learn
Docker
AWS
SQL
Scrapy
We are AI/ML engineers
Computer Vision
NLP
Time-series analysis
Anomaly detection
Machine Learning
Deep Learning
Model optimization
