Jacob Avenaim

• Led analytics for 30+ Fortune 500 clients using Databricks, R/Python, and large-scale datasets • Built reusable pipelines in Databricks with GitHub and modularized R functions to streamline delivery • Used SQL to ingest, clean, and join data for modeling and feature engineering in Python/R • Delivered insights to stakeholders via Tableau dashboards and tailored PowerPoint reports • Mentored junior analysts on code quality, modeling assumptions, and client-facing communication • Worked cross-functionally with stakeholders to ensure alignment of data insights with business priorities • Enabled clients to track year-over-year trends and develop strategy based on key workforce metrics

• Analyzed external labor and business data to identify key trends, risks, and growth opportunities • Cleaned and integrated large-scale datasets using R and Python to build clear market and workforce views • Visualized workforce flows and transitions to uncover patterns in hiring, promotions, and exits • Supported scenario modeling to forecast business outcomes under various strategic assumptions • Built Excel tools and Tableau dashboards to surface site-specific insights for decision-makers • Contributed to client-facing presentations by translating analytics into clear strategic narratives

• Identified, and oftentimes implemented, potential solutions for challenges related to Macro-Economic Austrian problems • Worked a part of a team to help Austria make informed decisions related to improving their performance and realizing their most important goals. • Worked with economic data in R and Python to synthesize clear takeaways from complex information to help make informed recommendations using qualitative and quantitative methods • Worked effectively with diverse teams to come up with the best solutions and move people and organizations to act

• Worked in Jupyter Labs, using Python, to create a program that can systematically take any arbitrary number of files, regardless of file type and size, and then concatenate those files into a single file utilizing data wrangling and column matching • Worked collaboratively in a diverse team and created an inclusive environment with people at all levels of the organization • Drove an independent workstream in the context of a broader team project • Developed a comfort with an ambiguous, ever-changing situations • Communicated effectively, both verbally and in writing, with all audiences, including senior leaders, in a structured manner

• Structured an ambiguous problem and took actions to solve it • Extensive research to find schools exercising no-loan financial aid packages in the US (United States) • Initiated contact with school financial aid departments to compile data • Organized data into an excel spreadsheet for statistical analysis • Weekly communication with Professor regarding progress

• Initiated an average of 50 calls a day to pitch firm’s debt-relief services to prospective clients • Professionally explained how the formal financial investigation leads to an affordable payment plan in which debts can be settled and answered questions by phone and email • Collected information from clients via telephone interviews and assembled necessary documentation • Created Excel spreadsheets to analyze monthly income and expenses to determine disposable income and performed comparative analysis of client’s income data with federal standards • Utilized Logics daily to correspond with senior tax professionals and schedule meetings to discuss my findings • Revamped company website using both Wix and Java

• Identified five potential empty lots in the Chicago area for potential development • Used PowerPoint to create 3D detail-oriented presentations for each property consisting of overhead pictures of property, listing all nearby properties, both aerial and local views for use • Presented data to executives for potential investments • Compared and contrasted data for various projects and analyzed for inconsistencies • Analyzed licensing and insurance certificates