SYED HASAN

859-***-**** adj3fr@r.postjobfree.com https://www.linkedin.com/in/hasansi https://github.com/hasansi

TECHNICAL SKILLS

• Microsoft Excel(Pivot Tables, Macros, VBA), SSIS, Power BI, Python, C++, MySQL, NumPy, Scikit-learn, Pandas, NLTK, Keras, PySpark, MLlib, Matplotlib, Seaborn, Dimple.js, Javascript, HTML, CSS, Beautiful Soup, Flask, Git, GCP, AWS(EC2, Lambda, API Gateway, S3, DynamoDB),

EDUCATION

2017 – 2018: Udacity Nanodegree in Data Analyst

2007 – 2016: University of Kentucky PhD in Physics

•Performed regression analysis on radioactive source data from silicon detectors using Python and Root, for detector calibrations at the Los Alamos National Lab.

•Ran all aspects of the Ultra Cold Neutron B experiment, including setup, calibration and instrument adjustments. This experiment resulted in improved position sensitivity, signal to noise ratio, resolution, and timing of the Lab's detector system.

•Wrote code in C++ to perform simulation of experimental conditions.

•Author of 5 peer-reviewed publications and 3 invited talks.

2007 – 2010: University of Kentucky M.S. in Physics

•Physics Merit Scholarship and Gold Medal recipient.

EXPERIENCE

2020-Present: Data Science Freelance, https://www.hasanalytics.com

•Performed ETL in SSIS on sales data and created report to gain insight into business performance.

•Movie Recommender Web App (bit.ly/pop_flix): Built an NLP content based recommender based on ETL performed in Python on structured and unstructured data obtained from a variety of sources.

•Classified client's customer churn, using logistic regression in MLlib and PySpark.

•Predicted the fraction of client's customer loan that would be delinquent by the end of the loan term, using polynomial regression with a mean squared error of 2.4e-8.

2019-2020: Data Science Fellow, SharpestMinds

•Product Sentiment Analysis Web App (bit.ly/twittersent): The App collects live tweets about a product and determines an overall positive or negative sentiment expressed towards that product using the Twitter API, NLTK.

•Spam Filter: Built an NLP pipeline to identify Spam text with 93% accuracy.

2016-2020: Quality Engineer, Webasto

PERSONAL PROJECTS

•Wrangling OpenStreetMap Data: Extracted, audited, cleaned and transformed data, about my city of Lexington-KY, in XML format to CSV and then queried the data using SQL and produced a visualization of interesting facts like most popular cuisine, amenities and shops.

•Identifying fraud using Enron data: Identified fraudulent employees at Enron using various machine learning techniques and algorithms with the final model yielding 89% accuracy and 65% precision despite having 45% data missing.

•Forensic Cluster Analysis: Identified number of hackers using K-means clustering on session meta data, in PySpark.

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