About

Hey there, I'm Ankur Patel

I am a diligent researcher with a passion in data science, motivation in healthcare, and ambition in business. A B.S. in Biomedical Engineering from UAB and industrial research experience has geared me towards a data science career. I recently graduated with a M.S. in Data Science. On an average day, you will probably find me doing one, if not multiple, of the following: meeting clients for consulting projects, attending meetups, or participating in hackathons. Other than that, I enjoy exploring new cities, tasting new flavors and dishes from different cuisines, and watching an assortment of movies. I believe the best way to grow is to open the mind to learn and understand every part of the seen and unseen world. The key is to stay curious.

Checkout my resume

Activities besides tech

Contact me here!

Email: p.ankur.715@gmail.com

Phone: 251-447-6255

Experience

Data Engineer - Greater New York Insurance Companies

  • Develop, construct, test, and maintain architectures, such as databases and analytic environments and platform required for structured, semi-structured and unstructured data.
  • Design and develop data pipelines that deliver accurate, consistent, and traceable datasets for data science projects.
  • Support regular and ad-hoc data needs for data scientists.
  • Provide recommendations and implement ways to improve data reliability, efficiency, and quality.

Aug 2020 - current

Data Engineer - Executive Business Solutions Corp, NYC

  • Developed data pipelines for ETL from sources’ APIs, deploy in AWS EC2 with scheduler, load to RDS SQL, analyze on Tableau, and create sales predictive model.
  • Created SQL Server database for clothing retail client, performed customer segmentation on purchasing habits, created KPI’s for business process improvements.
  • Trained clients for Finance Analytics modeling with timeseries data for stock returns, volatility, OLS, back testing.
  • Supported clients projects in customer segmentation, geospatial analysis, and Tableau dashboards.
  • Taught bootcamp courses for Data Analytics and Machine Learning using Python, SQL, R, Excel, Tableau.

Oct 2018 - Mar 2020

Independent Study – Business Assessment Scores Using Yelp Reviews - Verisk Analytics, NJ

  • Developed an assessment score using business and reviews json files from Yelp challenge dataset.
  • Created LDA model for topic modeling and stars after inspecting topics using pyLDAvis, and a domain specific lexicon for scores that were normalized across NAICS Codes and social networking sites.
  • Deployed model for user interaction using Flask API.

Sept 2019 - Feb 2020

Forecasting & Business Analysis Intern - Novo Nordisk, NJ

  • In a Financial Planning & Analysis team, processed and analyzed big data of pharmaceutical products’ volume with forecasting software and model, and visualize in Tableau.
  • Developed ETL program in Python to map and integrate databases and execute with a model.
  • Developed a Tableau dashboard to demonstrate Anchor Budget and Rolling Estimate forecasts.

Jun 2019 - Aug 2019

Data Analyst - InSpirAVE, NYC

  • Analyzed e-commerce data of products and prices of selected merchant partners, compared with competitors, and collaborated with other e-commerce businesses.

Jan 2019 - Feb 2019

Researcher II - UAB Medicine, AL

  • Collected mice colonies’ bodyweight, genotypes, glucose/insulin/pyruvate tolerances, proteins and analyzed using Excel, R, and Python.
  • Managed lab inventory and ordering.

May 2017 - Aug 2018

Research Assistant - Dynamic Biosciences LLC, AL

  • Performed analytical testing procedures for breweries and reported results to customers.
  • Managed the company’s sales of laboratory equipment.
  • Assisted in column chromatography and performed a mass spectrometry assay to measure purity.
  • Created graphs of the data in Graphical Analysis software.

Aug 2016 - Dec 2016, Jan 2015 - May 2015

Training

ELCHackathon 2019 - ELC Recycle Rewards Kiosk

Group won first place for developing an Amazon Echo app to interact with customers to offer rewards and an option to donate for recycling ELC products, by using an infrared sensor and LED display to identify the item. The software used were Vision API, Cloud SQL, and Python.

Sep 2019

Redline Hackathon 2019 - Seeker

Group won 2nd place for developing a SaaS app called Seeker that uses Google Cloud Video Intelligence API for object detection and time intervals, and Yuuvis for storage and Search Service API to jump to time of searched object.

Apr 2019

HackFest 2019 - SaferWay

The first routing app that provides the safest routes by using ArcGIS API and city wide traffic statistics. The app works by predicting the probability of vehicle crashes at a certain location given several inputs like precipitation chance and amount, temperature, time of day, past crashes, and sinuosity of the road.

Apr 2019

Global Legal Hackathon 2019 - Violence Reporter

Competing against 6000 participants from 24 countries, team created an audio and image classification app to notify users of real-time and location-based crimes for evacuation and for lawyers’ use during claim cases.

Feb 2019

NYC Grand Hack 2018 - MobileAI

MobileAI phone app of image or video classification to assist visually impaired users in independent mobility through real-time navigation by capturing location from the pre-trained model.

Nov 2018

Education

Bachelor of Science in Biomedical Engineering - University of Alabama at Birmingham

Birmingham, Alabama

Aug 2012 - May 2015

Master of Science in Data Science - Saint Peter's University

Jersey City, New Jersey

Sep 2018 - Feb 2020

Portfolio

Checkout a few of my projects

Mar 2020

Finance Analytics

Analyzed time-series data of stocks for stock returns, volatility calculations, OLS, back testing, predictive, along with quantopian research.

Python

View Project

Apr 2019

AWS Redshift Cluster Analysis

Extracted data from ZAGI database in PostgreSQL server, load into AWS S3, then Redshift using Python

Program: PostgreSQL, Python, S3, Redshift

View Project

Oct 2019

Heart Disease Risk Factors

Employed machine learning, ensemble, and statistical analysis for feature selection and tuned models for predicting heart disease with 93% accuracy

Program: R

View Project

May 2019

Twitter Sentiment Analysis

Analyzed tweets of 2020 Democratic Presidential Candidates from Apr 4-11 uniformly by state, and tweets from the candidates' personal Twitter accounts from Nov 1 - Mar 31

Program: R

View Project

Feb 2019

Neural Networks

Multilayer perceptron (feed forward neural network) with hidden layers on iris dataset; CNN for image classification in MNIST, SVHN, and pet dataset

Program: Python

View Project

The Truth

A day in the life of a data scientist

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