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Analytics and Security at ServiceNow
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Experienced data professional in designing and building advanced data analytics solutions from inception. Analytical problem-solver with a detail-oriented and methodical approach. Overall 10+ years of experience in the field of Data Engineering and Science. My contact information: abhinav.tomer27@gmail.com
The University of Texas at Dallas
Master’s Degree, Data Science
January 1, 2016 – January 1, 2018
APJ Abdul Kalam Technological University
Engineer’s Degree, Computer Science
January 1, 2008 – January 1, 2012
ServiceNow
Analytics and Security
January 1, 2022 – Present
Austin, Texas, United States
Autodesk Construction Solutions
Senior Data Engineer
September 1, 2020 – January 1, 2022
San Francisco Bay Area
Autodesk
Data Architect
February 1, 2019 – September 1, 2020
Autodesk
Data Engineer
June 1, 2018 – February 1, 2019
Autodesk
Machine Learning Research Intern
November 1, 2017 – May 1, 2018
Autodesk
Data Scientist Intern - Forge Data Analytics team
May 1, 2017 – November 1, 2017
HCL Technologies (Infrastructure Services Division)
System Analyst
July 1, 2013 – February 1, 2016
India
Analyzing effect of drinking laws on vehicle fatality
January 1, 2017 – April 1, 2017
• Designed Fixed Effects and Time Fixed Effects Model for Panel data to analyze the effects of drinking laws on vehicle fatality rate • Implemented Random Effects and Fixed Effects model to examine the impact of change in beer tax on young age drivers vehicle fatality rate
Big Data Analytics Project
January 1, 2017 – April 1, 2017
• Merged and cleaned the data set using Hive Queries and Pig Latin Scripts in HDFS • Designed machine learning models such as Neural Networks, Logistic Regression and Support Vector Machine using pyspark to predict whether the firm will file bankruptcy • Designed an automated model to classify emails as spam or not spam using Text Analytics technique in Python
Marketing Project - Increasing T.G.I. Fridays revenue
January 1, 2017 – April 1, 2017
• Segmented the customers into different clusters according to revenue generation, age, frequency of visit, time of meal • Performed Survival analysis to increase the frequency of customers visit for different segments • Implemented elasticity modeling to predict the price change for different segments to maximize the revenue
Recommender Engine – Python Programming
January 1, 2017 – April 1, 2017
• Segregated users into adult or child using Classification and Clustering algorithms by analyzing the JSON log data • Developed a recommender system for Cloudera Movies using python in HDFS on Map Reduce execution engine.
Machine Learning
November 1, 2016 – Present
• Performed data cleaning to prepare it for analysis using Pandas Library in Python by imputing missing value and checked data for outliers • Programmed analytical model in Python using ScikitLearn and Numpy packages in Jupyter Notebook to segregate Iris flowers data set into three categories using Classification and Clustering • Automated the model to recommend rating of products by utilizing users reviews with Natural Language Processing
Analysis of NBA Season 2014 - 2015
August 1, 2016 – November 1, 2016
• Created predictive model for NBA coaches to strengthen strategies for winning a game using Decision Tree, Logistic Regression, and Model Comparison to predict best conditions for scoring a basket with accuracy of 95% • Developed a Linear Regression model for team management capable of predicting the performance of players, listing best shooters and best defenders, All-Star team, and most valuable player for next season
Creating Data Warehouse for Glassdoor
August 1, 2016 – November 1, 2016
• Outlined E-R model and Data model for website Glassdoor using Erwin to define schema for record retrieval and converted it to physical database using SQL Server Express 2014 for data storage • Designed Data Universe using SAP Business objects BI4.1, built reports using Web Intelligence, and created visualizations and interactive dashboards using Tableau
Intermediate Python for Data Science
DataCamp
June 24, 2026 – Present
Pandas Foundations
DataCamp
June 24, 2026 – Present
Manipulating DataFrames with Pandas
DataCamp
June 24, 2026 – Present
Supervised Learning with Scikit-Learn
DataCamp
June 24, 2026 – Present
Certificate in Network Management
Nettech Private Limited
June 24, 2026 – Present
ITIL® v3 Foundation 2011
AXELOS Global Best Practice
June 24, 2026 – Present
Microsoft Certified Solutions Associate 2012 Server
Microsoft
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio is diverse, covering areas like marketing, finance, sports analytics, and recommender systems, indicating a broad interest and adaptability. The career progression from Data Engineer to Data Architect and then to Analytics and Security suggests a growth mindset and ability to take on increasing responsibilities. The target role of Data Analyst aligns well with the candidate's project experience in statistical analysis, predictive modeling, and visualization. The certifications in Pandas and Scikit-Learn further demonstrate a commitment to continuous learning relevant to data analysis. The shift from Data Engineering/Architecture to a Data Analyst target role might require clarification on career aspirations.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse problems and apply various analytical techniques. The progression through Data Engineer, Senior Data Engineer, and Data Architect roles at Autodesk suggests a strong operational understanding of data pipelines and governance. However, without specific psychometric test results or interview data, it's difficult to assess soft skills like teamwork, communication style, or stress handling directly. The experience as a System Analyst at HCL also points to operational experience in IT services.