Sep 2022 – Nov 2024 · 2 yrs 2 mos · Gurugram, Haryana, India

• Leading analytics for a product analysing organization structure using client and internal HRIS
• benchmark data.
• Developed product’s business value proposition, metrics, and presentations resulting in over 20 clients
• engagements within 6 months, helping them in making critical business decisions
• Streamlined onboarding processes, codebase, standard operating procedures and maintained data integrity directly
• resulting in reduced delivery timelines by 50%.
• Spearheaded analytics for an award winning McKinsey analytics report involving analysis of global talent - https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech
• market using over 350M job postings and over 60M linkedin profiles - McKinsey Technology Trends Outlook 2023
• Worked on 50+ client projects involving people analytics and peer comparision of talent market using
• linkedin profiles, glassdoor reviews and job postings data which helped clients make critical business decisions

Sep 2020 – Aug 2022 · 1 yr 11 mos · Gurugram, Haryana, India

• Helped finalise and interview candidates for both senior and junior levels in
• the data science team for the company
• Initiated and led the hiring of interns for data science team for a 10 week
• internship directly under me
• Developed and led the deployment of customer churn model
• Setup the big data warehousing using Redshift and SQL that we have currently at the company
• Analysed user participation and fatigue in games, created and classified games into 4 categories. Games transferred on my suggestion are now the
• best performers in battles by a factor of 8x
• Assisted in game cheating prediction data analysis and deposit prediction
• data collection. This analysis was used in improving model accuracy and
• model building

Jul 2020 – Sep 2020 · 2 mos

• Worked on Anti-COVID AI. Mask detection, people tracking and reidentification
• Social Distancing using computer vision
• Built multi object generic tracker capable of tracking any object and reidentification of people in case of rentry into the frame and face occlusion
• Solution built was demoed to various prospective clients

Jan 2020 – Jul 2020 · 6 mos

• Worked in Computer Vision Team to build end to end solution for face detection and recognition
• Solution also involves face re-identification and tracking across camera angles with face spoof detection
• Designed process for collection of face spoof data
• Worked on Intel OpenVINO platform to test various pre-trained models and speed up using their inference engine
• Worked with third party labelling services to get data labelled
• Evaluated pre-trained models along with various versions of custom built tracker on customer data

Aug 2019 – Jan 2020 · 5 mos

• Worked in Computer Vision team on face detection and recognition tasks involving literature review, landmark detection and labelling of data
• Tested and trained various models for face detection

Jun 2019 – Aug 2019 · 2 mos

• Worked in Computer Vision Team and used real time object detection to built real time queue management algorithm
• Labelled, cleaned images and built dataset for real time person detection and checkout counter detection using YOLOv3 model
• Deployed algorithm on NVidia’s Jetson Nano

Aug 2018 – May 2019 · 9 mos · India

• Organised Hack-O-OWASP as the Overall Student Coordinator. Theme was Build for India by PayTM with Vice President of PayTM as Chief Guest
• Taught Machine Learning and Deep Learning to 1st and 2nd year students. Topics included :
• 1. Linear and Logistic Regression with parameter insight
• 2. Neural Networks with Backpropagation
• 3. Convolutional Neural Networks