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Data analyst

Location:
New York City, NY
Posted:
October 19, 2020

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Resume:

New York, NY 631-***-**** adg3w4@r.postjobfree.com LinkedIn GitHub Portfolio

Initiative-taking analytical mindset with a strong dedication for continuous learning and intellectual growth. Offering experience of collecting and preparing/cleaning data, applying statistical analysis to deliver valuable insights, and building predictive models using solid Python programming skills. SKILLS

• Languages: Python, R, SQL, HTML, CSS, JavaScript

• OS: Windows, Linux (Ubuntu 18.04)

• Shell: PowerShell, Bash

• Frameworks/Libraries: Pandas, NumPy, SciPy, Statsmodels, Sci-kit Learn, Keras, NLTK, Gensim, Matplotlib, Seaborn, Plotly, Flask

• Technical Skills: Data Collection, Data Wrangling/Cleaning, Exploratory Data Analysis (EDA), Hypothesis Testing, Statistical Analysis, Deep Learning, Machine Learning, Regression, Classification, Clustering, Version Control (Git)

DATA SCIENCE PROJECTS

Disaster Response GitHub Web-App Nov 2019

• Utilized frameworks such as NLTK and Scikit-Learn to perform ETL, build ML pipeline, and deploy ML model to a local web application.

• The ML pipeline processes 26,000 raw text messages using NLTK and Scikit-Learn to build a multioutput classification model.

• Maximized F1 score through feature engineering and parameter tuning. Solar Array Cost Prediction GitHub Blog July 2019

• Analysis revealed a trend of declining national average installation costs of about 30% since 2009 peak.

• Predicted the cost of a residential solar panel array using a ML pipeline built using Scikit-Learn.

• Evaluated multiple regression models (Ridge, RandomForest, GradientBoosting) and optimized the pipeline to minimize the RMSE and MAE.

EXPERIENCE

Field Engineer, Certus Controls, LLC, New York, NY Sep 2014 - Present

• Implementation of HVAC control strategies and development of graphical controls to accommodate the operator/end-user in high value Manhattan buildings.

• Managing and improving client relations, collaboration with clients to address concerns, troubleshoot, and resolve technical issues.

• Ensuring successful project completion, including time/resource management and training new staff members.

• Identifying areas of improvement and providing recommendations to management. EDUCATION

B.S Mechanical Engineering, Hofstra University May 2011 Introduction to Data Science, Springboard – Certificate Jan 2018 Python 3 Programming, Coursera – Certificate May 2019 Data Science Nanodegree, Udacity – Certificate March 2020 Sergey Mouzykin



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