SAAYED ALAM
**** ***** **. *** **, Bronx, NY, ***62, USA
saayedalam.com
@saayedalam
**********@*****.***
linkedin.com/in/saayedalam
github.com/saayedalam
US Citizen
Data Analyst with 3 years of experience in Finance. Data Scientist specializing in Data Analysis, Machine Learning and Deep Learning. Proficient in a range of technologies including Python, R, SQL and Apache Spark. Recognized for being personable, diligent and insightful. SKILLS
Technology Skills (Python, R, SQL, Hadoop, Spark, MongoDB, TensorFlow, Git, JSON) General Skills (Analysis, Visualization, Probability & Statistics, Multivariate Calculus & Linear Algebra, Machine Learning, NLP, Deep Learning)
EDUCATION
CUNY School of Professional Studies
Master of Science : Data Science
August 2018 – December 2019
New York, NY
New York City College of Technology
Bachelor of Science : Applied Mathematics
January 2016 – December 2017
Brooklyn, NY
Dean's List (Spring 2008, 2012, 2013 and Fall 2014, 2017) New York City College of Technology
Associate of Science : Computer Science
January 2014 – December 2015
Brooklyn, NY
PROFESSIONAL EXPERIENCE
preCharge Risk Management Solutions
Data Analyst
July 2013 – August 2016
New York, NY
Promoted from Office Administrator to Junior Data Analyst in less than 6 months. Addressed data collecting system issues to enhance usability and improve functionality. Collaborated with team members to discuss fraud trends and brainstorm methods to combat fraud. Analyzed 1000 customer's data daily to find patterns of fraud and anomalies. Completed quality assurance reviews to assess the accuracy of data and made actionable recommendations based on data trends.
PROJECTS
Predicting Fraudulent Online Transactions
Applied feature engineering and LightGBM gradient boosting algorithm in Python to detect fraud from customer transactions.
Sentiment Analysis of 2019 Australian Election
Worked with a team to perform sentiment analysis of Twitter during 2019 Australian Election and discovered the election was a surprise which led many to react negatively after the election. GoodReads Recommender System
Implemented a recommender system of a large dataset in Apache Spark and Python to recommend books based on GoodReads ratings.