Kaivon Ahmad

Data Scientist

New York, United States


I'm a tenacious problem solver who is eager to contribute to fascinating technologies with data driven approaches.



Favorite Python Packages:

Pandas, Numpy, Scipy, Scikit-Learn, Tensorflow, Keras



Bubo, Data Scientist, Switzerland (Remote) Nov 2017 ‐ Current

  • mined the API's of Youtube, Spotify, Apple Music, etc. to determine market size of particular startup venture observing user listener/views data
  • building unsupervised models to extract sentiment with scraped comments data
  • collaborating in team of 4

Airmed, Data Analyst, San Francisco Nov 2017 ‐ Jan 2018

  • developed data cleaning script with Python to process accelerometer data from wearable sensors
  • collaborated in a team of 3 with git version control

Soleeva, Associate, San Jose, CA Apr 2017 ‐ Nov 2017

  • designed a proposal tool that interactively visualizes and summarizes the economic benefits of going solar for homeowners

UCSF Diabetes Center, Staff Research Associate II, San Francisco, CA Sep 2016 ‐ Sep 2017

  • analyzed gene expression from DNA microarray
  • developed different clustering models
  • created interactive heatmaps using plotly


Parkinson's Disease Digital Biomarker DREAM Challenge Aug 2017 ‐ Sep 2017

  • extracted features from raw sensor (accelerometer, gyroscope, and magnetometer) time series data recorded during the performance of pre-specified motor tasks obtained from research-grade wearable sensors, smartphones
  • developed a machine learning model predict the diagnosis of Parkinson's Disease with an accuracy of 94%

Observing Similarities in Tumor formation from Cap Analysis Gene Expression Jul 2017 ‐ Aug 2017

  • explored overlapping gene expression profiles between various types of tumors, both benign and malignant
  • extensive wrangling of data acquired from Cap Analysis Gene Expression (CAGE) from human samples by the FANTOM5 consortium
  • utilized dimensionality reduction through Principal Component Analysis (PCA) and applied different clustering models including K-Means and Agglomerative


Amazon Web Services, Data Science, Git, Machine Learning, Natural Language Processing, NumPy, Pandas, PostgreSQL, SciPy, Spark, TensorFlow, Visualization, Web Scraping

Joined: March 14, 2018

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