Ajay Singh

AI Researcher

Delhi, India12 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led data science initiatives at Bajaj Finance.
Implemented models increasing lead conversion rates significantly.
Developed algorithms reducing operational costs in logistics.

Stackforce AI infers this person is a Fintech and Logistics data science expert with a strong focus on machine learning and analytics.

Contact

Skills

Core Skills

Data ScienceMachine LearningBusiness Intelligence

Other Skills

PySparkMicrosoft AzureXGBoostData AnalysisRevenue GenerationFacial RecognitionProbability TheoryDBSCANPhoneticsCHAID AnalysisRisk AnalyticsGPS Data AnalysisRandomForestSVMNaive Bayes

About

Ajay is a seasoned data science professional with a decade of expertise in machine learning and business intelligence, skilled at transforming data into strategic business insights. Currently, he is leading a team of 6 at Bajaj Finance Ltd., the biggest NBFC in India, enhancing app metrics and lending operations through in-app personalization, product recommendations, and cross-functional data strategies using extensive user clickstream data. Before that, Ajay spent five years as a data scientist at Delhivery, India’s leading logistics company, addressing complex supply chain and optimization problems. His diverse expertise enables him to deliver actionable insights and strategic solutions, making him a strong candidate for advancing data-driven initiatives in the finance sector.

Experience

Bajaj finserv

3 roles

Principal Data Scientist

Promoted

Apr 2023 – Present · 2 yrs 11 mos · On-site

Leading digital analytics and data science efforts for digital lending businesses

PySparkMicrosoft AzureData ScienceMachine Learning

Senior Lead - Data Science

Oct 2021 – Apr 2023 · 1 yr 6 mos · On-site

· Personal Loan Propensity Model - Implemented an XGBoost model utilizing the app, clickstream, and bureau data to enhance explicit lead conversion rates, elevating them from 8% to 12% for PLCS
· SALPL Lookalike customers - Utilized contact details, email domains, EPFO data, and appography to
identify salaried customers for PL, resulting in an additional 155 crore revenue on the app and web platforms. Simultaneously, achieved a reduction in the Cost of Acquisition (COA) from 4.5% to 3.5% per disbursal
· Developed and deployed highly accurate facial recognition algorithms (including VGG19 and RESNET),
reducing manual document verification process costs by 40%

PySparkMachine LearningData Science

Lead - Data Science

Feb 2020 – Sep 2021 · 1 yr 7 mos · On-site

· Deployed a DBSCAN-based GPS clustering algorithm to pinpoint customers’ current locations, sub-
sequently refining the clusters with CPV and receipts data. This initiative has resulted in several impactful
outcomes, including Skip Tracing of delinquent customers ( 15Cr saving), a 9-12% reduction in Match Rates for RCU [for Ecom], enhanced lead mapping of customers to Field Officers, and resolution of PL-OGL cases
to generate an additional 150 Cr, among other benefits
· Customer’s Primary Number Tagging - Designed a name prediction algorithm based on phonetics, lever-
aging the contacts data within the app to accurately identify primary and secondary contact numbers for
engaging with BFL’s prospects. This initiative significantly reduced wrong number (WN) tagging and in-
creased the success rate of Right Party Calling (RPC) from 76% to 91%.
· Risk Analytics B2B: Conducted multiple Design of Experiments (DOEs) utilizing CHAID analysis to tran-
sition approx 79L customers from New to Bajaj (NTB) to Prospects to Bajaj (PTB) offer pool for B2B

PySparkProbability TheoryData ScienceMachine Learning

Delhivery

2 roles

Data Scientist

Apr 2016 – Feb 2020 · 3 yrs 10 mos · Gurgaon, India

· Built a system to predict the path taken by a bike using mobile GPS data. Used ML algorithms to resolve GPS issues, e.g. missing GPS, irregular GPS points, U-turn behavior, etc. This path is being used in Automatic Fuel Payout of delivery agents and helped in saving INR 10M per month.
· Trucks ETA Prediction - Developed and deployed an algorithm basis RandomForest to predict the ETA of a Truck using GPS data. Finally, missing roads found during this were contributed to OpenStreetMap.
· Address Type Prediction - Implemented SVM and Naive Bayes to classify houses as residential or commercial using their address.
· Locality Polygons - Created geographical boundaries of cities and localities using DBSCAN, OSRM and tagged geopoint data with roads as solution space.

Probability TheoryData ScienceMachine Learning

Developer

Mar 2015 – Mar 2016 · 1 yr · Gurgaon, India

Converted Delhivery’s operations lifecycle into a time-based network graph and worked on suggesting shortest paths, alternate paths, reducing misroutes, etc.
Generic-wrapper: Developed a Queue-based API service architecture to serve millions of requests to time-consuming ML algorithms.
Naksha: Developed an algorithm to derive intelligence, eg. geofencing, routing etc. from GPS data and developed microservices around it. These polygons were later stored in the address hierarchy of state, city, locality, and sub-locality to assist in geocoding and reverse-geocoding process.
Catalog-UPI: Collected data from many e-commerce sources. Tweaked scoring mechanism of ElasticSearch to find the closest match of a new product. Created flow for manual verification of all attributes of a product to be able to uniquely identify products from an internally developed category tree.
Developed various internal tools. e.g. Locality Management, Cataloging, Report Central.

Payu india

Software Engineer

Aug 2013 – Feb 2015 · 1 yr 6 mos · Gurgaon

Part of the development team of New Merchant Panel for PayU's merchants to monitor/analyse their transactions traffic and display result using pie charts and graphs.
Integrated banks with payment gateway to facilitate direct transactions while strengthening the end-to-end security of its Internet banking services.
Developed various web services and customization options for payment flow for merchants.