Jan 2024 – Present · 2 yrs 2 mos · Gurugram, Haryana, India · On-site

• 1. Applied AI/ Gen AI Education to bridge the gap b/w Industry & Academia
• 2. Building Sales Network across the Globe
• 3. Fractional CXO role supporting multiple start ups
• 4. Corporate Trainings - AI / Gen AI for CXOs.

Jun 2022 – Dec 2023 · 1 yr 6 mos · Gurugram, Haryana, India

• Key Highlights:
• 1. Accelerated revenue growth, achieving ~40% YoY expansion in Data Analytics for Strategy & Transactions.
• 2. Led a powerhouse of 200+ AI & Data Science team delivering cutting-edge AI solutions across industries.
• 3. Pioneered Generative AI innovation, transforming Strategy & Transactions with next-gen AI capabilities.
• 4. Institutionalized AI best practices, enabling scalable, enterprise-grade innovation and service excellence.
• 5. Enabled X-Competency & X-Service Line Collaboration, transforming M&A lifecycle with automation & insight

Jun 2019 – Jun 2022 · 3 yrs · Gurgaon, India

• Key Highlights:
• Powered Shine’s turnaround, transforming it from a loss-making company to EBITDA positive.
• Built & Scaled Data Science team, driving a data first culture across the organization
• Deployed AI at scale by effective collaboration b/w tech, product & data science
• Enabled B2B & B2C growth, leveraging data-driven insights for Recruiters, Candidates & Learning.
• Amplified Shine’s brand presence, strategically communicating key milestones to media & journalists.
• Business & Growth:
• Developed Renewal prediction Model to predict the likelihood of client renewing the existing product
• Model helped improving the Client renewal rate by ~50% helping revenue protection of ~ $$ 2 MM
• Digital Product Innovations:
• 1. CV Parser:
• Developed an in-house NLP based sectional CV Parser using AI & Deep learning algorithms to extract relevant entities from resume; It replaced the 3rd party CV Parser for entity extraction from resume
• Patent Application had been accepted
• 2. JD Parser:
• Developed an in-house NLP based JD Parser to extract relevant entities from JD using AI & deep learning algorithms
• 3. ARS (Application Relevance Score):
• Built ARS to develop a mechanism to score applicants to sort them based on their relevance to job postings; Helps Recruiters in screening & shortlisting candidates
• 4. Recommendation Engine:
• Developed a personalized recommendation engine to offer relevant courses & services to candidates basis their behavior & skill gap on Shine platform
• 3X increase in Add to cart
• 5. Job Alert Mailers:
• Developed a mechanism to recommend relevant jobs to candidates basis their profile & application behavior
• CTR got improved by 2X, # of sessions improved by ~75% & 2X increase in # of applications
• Data Governance & Compliance:
• Designed a cloud-based data strategy, enabling scalable AI deployment across the organization.
• Ensured enterprise-wide compliance, reviewing and approving all regulatory adherence initiatives.

Apr 2017 – May 2022 · 5 yrs 1 mo · Gurgaon, India

Feb 2017 – Jun 2019 · 2 yrs 4 mos · Gurgaon, India

• Led a team of data scientists & data engineers working on product development, AI infusion in products/process, text/NLP advancements, mainstreaming machine learning at core, Image/Video Analytics implementation, Proof of concept delivery ownership, open source adoption and leading data science trainings.
• Digital Product innovation:
• ➢ IMAGN
• o Developed an inhouse image analytics product “ÏMAGN”. It uses Machine Learning(SVM) and Deep Learning(CNN) to automatically identify damaged area from drone captured rooftop images and estimates the insurance claims damage.
• o IMAGN is developed as one stop solution for image analytics. It would be used for social media analytics and extensively for insurance, healthcare, retail & CPG verticals
• Sales & Business development:
• o Devised strategy for smart collection for Utility client which helped winning largest utility deal with TCV of ~ $$ 27 MM.
• o Developed the Image Analytics solution for a Top 5 US insurance firm, which was adjudged the best among all the competitors.
• Proof of concept (POC) delivery:
• o Market Mix Model for a pharmaceutical firm – Development of MMM which involved the complex methodologies of SEM and finding intermittent variables along with the original variables impacting sales.
• o Fraud detection for a US Bank – Development of Fraud model to capture online fraud for a US Bank, This project helped us setting up Fraud detection team (5 FTE) in Gurgaon
• o Personality Trait identification for UK media firm– Identifying personality archetypes/Traits of 40k celebrities using social media data, News/blogs/forums data, Wikipedia, media mentions
• o 77 Categories classification for UK media firm– Deep Learning Algorithm was used for classification of given text (2 MM tweets) into 77 categories

May 2016 – Dec 2016 · 7 mos · Mumbai Area, India

• Key Highlights:
• 1. Pioneered a world-class Online Data Science Program, delivering AI education to the inaugural cohort.
• 2. Led End-to-End Technical Oversight, ensuring an industry-leading curriculum for real-world AI applications,
• 3. Designed & Delivered high-impact masterclasses, empowering professionals with advanced AI & ML expertise.
• 4. Taught a Specialized Banking Analytics elective, leveraging AI to revolutionize financial decision-making.

Mar 2016 – Present · 10 yrs · Cambridge, Massachusetts, USA

• Leaders Excellence is an exclusive online network at Harvard Square for mid- and upper-level management who want to grow as leaders and ascend to the next level of their professional career.
• The goal is to empower driven professionals to cultivate a robust network of fellow leaders, one that facilitates long-lasting and beneficial business relationships. It’s a holistic approach to developing stronger, more capable leaders who can lead successful organizations and contribute to a stronger global economy.
• Leaders Excellence is supported by some of the world’s most esteemed executives and professors from such prestigious universities like Yale, MIT, and Stanford. To preserve the integrity and exclusivity of our network, membership is offered on an invitation- or qualification-only basis.

Oct 2015 – Aug 2021 · 5 yrs 10 mos · Harvard Innovation Launch Lab, Boston, US

Aug 2015 – May 2016 · 9 mos · Pune Area, India

• 1. Assumed CTO Responsibilities Within the 1st Week of Joining, seamlessly leading a full-scale transition with immediate strategic and technical oversight
• 2. Orchestrated End-to-End Delivery of High-Impact Data Analytics Projects across Marketing, Risk, Social Media driving transformation across multiple domains & geographies

Jan 2015 – Aug 2015 · 7 mos

• Added 1st Banking logo for WNS in Australia beating 4 Analytics companies
• Led a team of Data Scientists to deliver High End Advanced Analytics Pilot Projects
• 1. Advanced Analytics pilot project for an Australian Bank
• o Developed 9 Logistic Models using 3 different techniques and 2 Survival Models (Cox proportional Hazard Regression) for the mortgage portfolio helping bank predict the monthly default probability of Retail/Business customers

Apr 2013 – Dec 2014 · 1 yr 8 mos

• Led the Advanced Analytics for BFS vertical managing multiple teams (3) comprising 50+ Advanced Analytics professionals spread across multiple locations (Gurgaon, Bangalore, Mumbai) in India for Super Regional US based Banks
• Helped setting up the Retention Analytics Team and Next Best Activity/Analytics Road map for UK Based Insurance client
• Core Member of Due diligence Team for Dubai based bank
• Launched a campaign targeting strategic US banks for analytics services and Developed BFS Analytics center of Excellence offerings for new BFS Prospects

Feb 2010 – Mar 2013 · 3 yrs 1 mo

• Developed the Best in class 20+ Advanced Analytics Team of Highly qualified Professionals (Mostly from IIT/ISI/DSE) from scratch for US based Bank
• Managed Functional units (Modeling, E Commerce & Web Analytics, CRM, Data Analytics) for all LOB (Auto Finance, Auto Auction, Mortgage, Deposit) for US based Bank
• Performed the dual role of Building the Advanced Analytics Team and working on various innovative complex Modelling projects as an individual contributor.
• 1. Survival Model (Cox proportional Hazard Regression) for Mortgage Portfolio
• o Developed a Survival Model predicting month-on-month default probabilities for customers opted for Mortgage Modification Plan
• o Reduced customer Attrition by 12% over one year timeframe resulting in revenue protection of $ 1.2 MM
• 2. Retention Response Model for Mortgage Portfolio
• o Developed a Logistic regression Model with dual objective of increasing response rates and restricting attrition rates at the same time
• o Revenue generation of $ 1MM due to reduction of sleeping customers by 10%
• 3. Next Best Product for Mortgage Portfolio
• o Developed 12 Logistic Models and 1 Multinomial Logistic Model for predicting customer’s likelihood of best Mortgage product/Transaction Type
• o Model helped increasing response rate by 30% resulting in revenue generation in the order of USD 2.5 MM

Aug 2009 – Jan 2010 · 5 mos · Hyderabad Area, India

• Developed Acquisition strategy
• o Developed Credit Index/Fraud Index using 4 different Model scores (Application score, FICO Score, Fraud score, ASA Score) and derived a Master Index for Product Assignment & Credit Limit Assignment
• Mentor for new/experienced hires for Modeling Techniques
• Initiated Statistics classes for R&A Team

Jan 2008 – Jul 2009 · 1 yr 6 mos · Hyderabad Area, India

• 1. Developed True Name Fraud (TNF) Model & Fraud Strategy
• Built TNF Model using Logistic Regression @ Acquisition phase; Used “Reject inferencing” to infer performance of Declined Population
• Reduced 30% TNF cases with revenue loss protection in the order of $ 1.5 MM
• 2. Developed Credit Limit decrease strategy
• CLD Strategy using HRT (High Risk Trigger score), Utilization and open to buy causing to lose no more than $ 8 of good sales for $ 1 of bad charge off avoidance.
• 3. Developed Authorization strategy
• Manual referral Authorization strategy that helped reducing referral volumes by 40% resulting reductions in loss exposure of $ 1MM and increased sales up to $ 12 MM

Jul 2007 – Dec 2007 · 5 mos · Hyderabad Area, India

• Developed Customer Segmentation for PowerSport Portfolio
• Solved the complexity of clustering project by improving the existing methodology and reducing the project time by at least 3 days

May 2006 – Jun 2007 · 1 yr 1 mo · Gurgaon, India

• Developed 20 best in class response Models using Supervised classification algorithms for various Cross sell/Up Sell offers for international markets (Mexico, Canada, Italy, UK, Japan and Australia) reducing marketing spend by ~ 50% and capturing ~ 90% responders
• Developed Best in class BT (Balance Transfer) Models for Mexico and Australia for the first time which were the highlights of Executive Dashboard for CXOs.