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Applied Data Science Manager | Machine Learning Engineer | Personalization | Growth ML @ Warner Bros. Discovery
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University of Southern California
Master of Science (MS), Computer Science (Data Science)
January 1, 2016 – January 1, 2018
PES Institute of technology
Bachelor of Engineering (B.E.), Engineering
January 1, 2010 – January 1, 2014
Warner Bros. Discovery
Engineering Manager - Applied Data Science
April 1, 2025 – Present
Warner Bros. Discovery
Staff Applied Data Scientist
March 1, 2024 – May 1, 2025
Warner Bros. Discovery
Senior Applied Data Scientist
June 1, 2022 – March 1, 2024
Warner Bros. Discovery
Applied Data Scientist II
May 1, 2021 – June 1, 2022
Women Who Code
Data science volunteer
May 1, 2020 – April 1, 2021
Walmart Labs
Applied Data Scientist
September 1, 2018 – May 1, 2021
Entefy
AI & Machine Learning Intern
January 1, 2018 – July 1, 2018
Palo Alto
University of Southern California
Machine learning grader
August 1, 2017 – December 1, 2017
Information Sciences Institute
Research Assistant
May 1, 2017 – August 1, 2017
Deloitte
Business Technology Analyst
August 1, 2014 – July 1, 2016
Bengaluru, Karnataka, India
Cisco
Intern
June 1, 2013 – August 1, 2013
Greater Bengaluru Area
Spatio-temporal tweet analysis
October 1, 2017 – Present
The aim of this project is to analyze geo-tagged tweets to analyze the sentiment variation over time and space. This helps to identify the days and time of day when people tweet happy emotions and when do they tweet negative emotions. Project involves data collection using Twitter RESTAPI, Visualization using Matplotlib and Spatial statistical analysis to confirm trends
Hybrid Movie Recommendation System
March 1, 2017 – May 1, 2017
Developed a hybrid Movie Recommendation System using concepts of Memory based Collaborative Filtering and Model based Collaborative Filtering. For the memory based approach, item-based filtering technique was implemented using item-item similarity matrix. Clustering of items was implemented from model based approach.
Spatial Analysis for Ranking areas within San Mateo for residential suitability
October 1, 2016 – December 1, 2016
The project aims at ranking areas within San Mateo county suitable for constructing new houses using multiple criteria GIS based analysis with Analytical Hierarchy Process. Project involves analyzing the key criteria for affecting sale of new homes and a suitable site by GIS layer overlap. I conducted spatial analysis using various feature classes available from US Census , California state and San Mateo county GIS portal with Esri's ArcGIS 10.4
Customer Behavior Analysis
August 1, 2016 – November 1, 2016
Study car preference data of 5000 individuals to understand the customer behavior and major factors influencing the choice The analysis can be used for customer segmentation The project includes data collection, data cleaning and data analysis through classification and clustering using advanced Excel and R
Customer Credit analysis
July 1, 2016 – Present
Developed a logit model that predicts the probability of a customer defaulting on his credit payment. Corresponding scores were developed for easier risk identification. The analysis and model development was done in R and advanced Excel
Insurance Loss Analysis
June 1, 2016 – Present
Academic project where I evaluated customer data from an insurance company to create a linear regression model that could predict the possibility of losses new customers could cause based on his personal information using advanced excel
Telecom Upsell Analysis
May 1, 2016 – Present
Academic project to analyze client preference data of telecommunication industry to predict percentage of customers who would opt for a service upgrade using logit regression. The project included data collection, data cleaning and data analysis. Tools- Advanced Excel, R
ABAP Development for Pharmaceutical client
May 1, 2015 – October 1, 2015
Developed SAP Adobe forms Developed data migration codes Handled object migration from legacy to new system and fixed defects raised due to system version mismatch
ABAP Development for Aviation Client
November 1, 2014 – April 1, 2015
Developed high-complexity objects involving data communication between SAP SNC and SAP ECC systems for a Aviation and Defense client Handled multiple change requests raised on objects developed by teammates. Maintained and analyzed project level defect tracker to help quality management process in the project
Cultural Fit Analysis
The candidate's project diversity spans academic research, industry applications (e.g., recommendation systems at Walmart and Warner Bros. Discovery), and even earlier SAP/ABAP development. This breadth, combined with volunteer work as a data science instructor, suggests adaptability and a willingness to engage in various technical and educational contexts. The clear focus on ML/Data Science in recent roles aligns well with the target ML Engineer role, indicating a strong interest and commitment to the field. The early career in ABAP development, while not directly relevant to ML, shows a foundational engineering background.
Soft Skills & Operational Fit
The candidate's career progression to an Engineering Manager role suggests leadership and team collaboration skills. Experience as a content creator and instructor for Machine Learning indicates strong communication and mentoring abilities. The project descriptions, while lacking specific details on collaboration or problem-solving approaches, imply an ability to work on complex analytical tasks. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.