Neil Pathak

Neil Pathak has worked in the data engineering and analytics field since 2010. In 2018, they began working as a Marketing Data Analyst for Endless Media, where they used Python to analyze and visualize data from web-traffic, social media platforms, and sales. Neil also assisted in deck preparation for investor pitching. In 2019, they worked as an Agricultural Scientist for TreeTown USA, where they created a random-factorial designed greenhouse experiment, collecting data of over 200 trials using Excel. Neil also managed a team of Agricultural Workers, giving instructions on chemical application rates and individual trial handling. In 2020, they worked as a Data Scientist for Bubbly & Merry, where they managed e-commerce data with SQL to build marketing strategies for customer flows and on-going sales. Neil also used Python on Pandas, NumPy, with MatPlotLib visualization libraries to present executives easy to read representations of trends and KPIs. In 2021, they worked as a Data Scientist I - Product Analytics for Policygenius Inc., where they coordinated with Product Managers on Power Analyses for A/B Testing setup, aligned on core initiatives of their products, presented Primary Analyses findings through Exploratory Data Analysis, and drove decision-making based off results. Neil also used Logistic Regressions, Decision Trees, Association Rules, and other Machine Learning approaches with Python to analyze user-behavior; identify high value features. Finally, they are currently working as a Data Engineering Analyst for Gabi, a part of Experian, since 2022.

Neil Pathak obtained a Bachelor of Science in Plant Sciences from California State Polytechnic University-Pomona between 2018 and 2020. In March 2020, they also obtained a Certified Data Scientist certification from General Assembly.