Joel Abrahams

Seasoned data analyst with high figure-it-out quotient and experience using data science to find useful insights and distributing
those insights with dashboards and automated reports. I have a consulting background in search engine marketing and

Data Analyst: CommerceHub (Acquired Mercent Corporation) January 2016 – September 2017
Design and build production-ready reporting applications and machine-learning models using CommerceHub’s proprietary
data assets.
• Developed and maintained automated reporting application with Python ETL scripts for extracting data hourly from Amazon
Redshift into Amazon S3 to be ingested into BI tools
• Architected, designed, and implemented a Redshift analytical schema to be used for BI tools (i.e. Tableau, Power BI, etc)
• Imported, exported and manipulated large Redshift data sets with multi-million-rows for the purposes of analytical reporting
• Wrote views, tables, subqueries, and user-defined functions for Redshift to support analytical schemas and workflows to
support end user requirements
• Monitored the impact and performance on SQL queries on Redshift within AWS Management Console to ensure availability for
process outside of the analytical workflow
• Resolved SQL performance issues on Redshift by modifying queries, refactoring data, or changing other analytical processes
• Built a product catalog reporting application using Python and a SQL Server database that integrated with a RESTful API
asynchronously to enrich partial product records and store the results
• Created and deployed SQL Server Analysis Services (“SSAS”) Tabular Models, created perspectives, made extensive use of
DAX calculated tables and measures to satisfy business requirements using the Microsoft Business Intelligence (“BI”) Stack
• Designed machine learning workflow in Python using Scikit-Learn Library to address the impact of product placement &
promotions on performance
• Engineered a prototype model to help identify product classification using scikit-learn and improved the quality of labeling
using semantic similarity with a Word2Vec model using the Gensim Python library
• Calculated customer, vendor, and product lifetime values in order to improve marketing effectiveness
• Predicted future sales through Bayesian structural time series analysis

Data Analyst: Mercent Corporation August 2015 – December 2016
Omni-channel online advertising strategizing, reporting, and analysis using Mercent technologies to provide value to
clients, operations, executives and managers.
• Researched and developed strategies of pay-per-click marketing programs (including Google, Bing, eBay Commerce Network,
etc.) and marketplaces (Amazon, eBay, etc.) for portfolio of clients, including several Fortune 500 & Internet Retailer Top 500
companies to grow their accounts by as much as 50%+
• Created, monitored and tracked daily and monthly ad spend budgets up to 1MM+ to meet client demand and ROI goals
• Determined through data analysis and modeling answers to greater BI goals, such as whether to focus on new or existing
customers, in stock product data and the relationship to sales, identifying the effectiveness of bidding strategies as they relate
to client metrics by category
• Identified efficiency trends and opportunities for growth across a client’s portfolio of platforms
• Designed and developed BI solutions that integrate with OLAP cube to improve client reporting and performance outcomes
• Assisted with search specific market/client analysis to power sales pitches, marketing materials and industry thought
leadership content
• Optimize marketing programs by analyzing performance based on ROAS (Return on Ad Spend), impression share, ad spend,
and various metrics
• Used of statistical inference to analyze large data (regression, classification, text mining, hypothesis testing, etc.)

Marketing Specialist: Mercent Corporation August 2012 – July 2015
Prepared marketing research for managers to distribute. Brainstormed, and drove ideas for online advertising campaigns and
improving marketplace data quality with the responsibility to create said ideas thereafter.

• Campaign build, optimization, and reporting for 15 client accounts (including enterprise-level) in a variety of industries, with a
particular emphasis in eCommerce
• Advanced Search Engine Marketing (“SEM”) tools and techniques, such as bidding strategies (automated and manual),
campaign types (dynamic search, dynamic remarketing, remarketing lists for search ads (“RLSA”), Google AdWords/Bing Ads
editor, etc.), ad copy testing, and data feed quality analysis
• Developed insights, guidance and and documentation of company’s SEM/Pay-per-click (“PPC”) best practices

Software and Programming Languages: Python (scikit-learn, numpy, scipy, pandas), R, SQL, AWS (Redshift, S3) Microsoft BI Stack
(SQL Server, SSAS, Power BI, Microsoft Excel)
Advertising Platforms: Google AdWords (and Editor), Google Analytics, Bing Ads (and Editor), IBM Digital Analytics (Formerly
Coremetrics), SearchForce, Marin
Machine Learning: classification, regression, clustering, feature engineering
Statistical Methods: time series, regression models, hypothesis testing and confidence intervals, principal component analysis and
dimensionality reduction

Hofstra University – New York 2006 – 2010
Bachelors of Business Administration, Marketing


2006 - 2010

B.B.A., Marketing at Hofstra University

  • Updated 5 years ago

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