Dhivya Ravindran

The global financial technology platform that gives you the power to prosper. Products - TurboTax, Credit Karma, QuickBooks, Mailchimp

As a Senior AI Scientist, I build and evaluate RAG pipelines to deliver tax content at scale and velocity for Intuit’s Consumer Group using AI.

The Midwestern supercenter chain with 500 supercenters, grocery stores, neighborhood markets, and express locations across six states (MI, IL, IN, KY, OH, WI).

As the Lead Data Scientist at Meijer, one of the largest retailers in the US (contracted through Deel), I was part of the Meijer RMN (Retail Media Network) team, which collaborates with CPGs and brands to place advertisements on Meijer’s digital and in-store properties.

• Designed and built a Sales Attribution Model utilizing log and gamma distributions to measure campaign impact on in-store and online Sales.
• Researched and evaluated Google PAIR as a method to enable the Meijer RMN advertiser to deliver personalized and retargeted ads offsite to our audiences without relying on third-party cookies, preparing for a future without third-party cookie support.

Helping brands around the world make the most effective work, in the most creative way.

As the Staff Data Scientist, I am leading a team of Data Scientists and Data Engineers that deploys 260k+ CRM emails per month on the Salesforce Marketing Cloud and a portfolio of AI/ ML projects to bring together the power of data, technology, and creativity to build brands and unlock transformational and meaningful customer experiences for client accounts that include Edelman Financial Engines, L’Oréal, AMC Theatres, SAS, UPS, Santander Bank, BMW, Circle and Veterans United among others at Performance Art, a specialist creative-data advertising agency and division of Interpublic Group (IPG).

• Pitched, won and built a Multi-Touch Attribution and Media Mix Model for Edelman Financial Engines to score the impact of paid and owned media channels, distribute conversion credit accurately, double attribution accuracy and simulate media mixes that optimize conversions/ ROAS on media investments.
• Pitched, won and built the SAS Fandom Score pilot, to algorithmically score music fans’ fandom using Spotify data and social mining.
• With DANCE, an AI product, I built a Creative Optimization Model to predict CRM creative performance before campaign deployment.
• With the Martin Agency, I worked on the UPS Impact Score Attribution Model to assess the attribution value for each marketing activity and find a performing marketing mix that maximizes ROAS and impact.
• Built a Sustainability Tension Maps product for Martin that uses NLP techniques to do Tension Discovery, Tension Scoring, Tension Ranking, Content Curation and Content Augmentation to bridge the gap between sustainable intention and action.
• Worked on the Santander Bank Wage Inequity Campaign to measure pay inequity.
• Designed a Leads Segmentation Model to improve leads quality and a Loan Recapture Prediction Model to predict loan recaptures after closing for Veterans United.
• Worked on the Circle Insights Engine to measure Brand Health including Brand Trust, Brand Loyalty, Brand Awareness, Brand Usage and Brand Efficiency for Circle.
• Worked on award-winning creative strategies to make SAS appeal to more Data Scientists - Superhero Popularity Prediction to create the ideal next superhero and Roblox New Game Design.
• Formulated strategies for BMW Munich for retraining the Next Best Vehicle Model and included recommendations that align with BMW’s 2030 sustainability goals like getting rid of the business rules that recommend owners vehicles of the same fuel type rather than BEVs and PHEVs.
• Worked on the Rolls-Royce pitch and designed the metrics to ensure RR remains a house of luxury using the RR House Proximity Score, RR House Affinity Score (similar to the CAS model for BMW), and the RR House Progress Score.
• Did vendor evaluations for procurement decisions for multiple vendors including Databricks, Shutterstock, InZata, Fivetran, CausaLens, Snowplow, Dash Hudson, Netbase Quid, Adverity, Hightouch, Meltwater, Meltwater APIs and Dow Jones.
• As a People Manager, I have a human-centered approach to managing people that includes forging strong relationships, unblocking blockages and avoiding micromanagement.

We place experienced, pro-bono technologists to work with government and organizations responding to moments of crisis, to quickly deliver critical services and infrastructure that support the needs of the public. We’re non-partisan, fast, and free.

• As an Advisor, I mentored and advised Project Leads on what it takes to deliver data and technology projects for Governments, on how to navigate bureaucracies, and on how to manage constraints and deliver tightly scoped projects.
• As a Pro- Bono Data Scientist, I built a first-of-its-kind immigrant services directory that centralizes services for 3 million immigrants living in Los Angeles County.
• As the Account Manager and Lead Scoper, I was involved with the creation of the technical scoping documents, establishment of strong relationships with the partners and placement of Product teams (Engineers, PMs, Designers and UX Researchers) for the City of Syracuse’ Innovation and Data Office, the City of St. Louis’ Department of Home Services and the City of St. Louis’ Elections Office.

The Only Platform you need to run Retail.

As the Data Science and Machine Learning Lead, I consulted at multiple data touchpoints within a San Jose, California-based retail startup- from Marketing to Product.

• Strategized and built a B2B marketing small business leads database with near-ideal accuracy using Google Places API and built a rule engine to weed out B2B leads that have limited propensity to convert.
• Built market insights to curate the marketing strategy for different customer segments in different geographies. Studied 27 verticals within the retail industry and identified new growth segments for the retail startup.
• Strategized merchant and validation DB rules to sanitize and standardize product data (including the product category, sub-category, product EAN/ UPC barcode, product name, description, image, etc) for seamless onboarding of new merchants and new products for existing merchants.

We use technology, innovation, AI, design, research, policy, connectivity and collaboration to make NYC future ready.

As an NYC[x] Innovation Fellow with the City of New York, I partnered with various city agencies to rapidly solve NYC’s problems with data.

• Partnered with the Mayor’s Office of Criminal Justice and developed the Hate Crime Index, a first-of-its-kind data product and algorithm built for NYC that scores the propensity of hate crime occurrences in the city. The index captures ~75% of all hate crime occurrences in the city by targeting ~50% of the police precincts.
• Partnered with the Mayor’s Office of Operations and built the NYC block sampling and route optimization algorithms for the NYC Street Cleanliness and Scorecard program. The algorithms facilitated and operationalized the collection of cleanliness data points for 17000+ additional blocks in the city annually, a 12x improvement for an effort designed to better the cleanliness-based quality of life for all New Yorkers.
• Built a Grant Funding Determination Engine using Machine Learning for the Department of Cultural Affairs, the largest municipal funder of culture in the US that determines $28 million in funds disbursed for ~2000 cultural organizations in NYC.

BankBazaar.com is the world's first neutral online marketplace for instant customized rate quotes on loans and credit cards. Shop for loans & cards just like you buy everything else now - online.

As a Senior Data Scientist, my job role had me build and manage projects at multiple touch-points within BankBazaar.Com- from the core product to operations and marketing.

• Built the world’s first Interest Rate Deviation Engine using Machine Learning that predicts the best customers that can be made eligible for an interest rate cut for Personal Loans. The application rate of customers doubled with rate deviation and the approval rate improved by ~5%.
• Built Partner Preference Engines for Credit Cards and Personal Loans that predicts the customer’s ‘applying’ behavior and the bank’s ‘approval’ behavior. These Machine Learning models are used in the ranking and ordering of product offers and the offer position improved by ~19% for applied offers and by 22% for approved offers.
• Built Application Prioritization Engines using Machine Learning that enables for efficient customer life-cycle. This was done by predicting an application’s approval probability for Credit Cards and loan disbursal probability for Mortgages, Auto Loans and Personal Loans. The engines capture 80% of all approvals/ disbursals by processing just 50% of applications.
• Designed and tracked multiple targeted and personalized campaigns for Auto Loans using exploratory analyses. The campaigns drove an additional ~6% application volume to the existing Auto Loan portfolio.
• Enhanced customer data assets by mining unstructured data sources. The data were classified into different types of transactions using Natural Language Processing techniques.
• Built Credit Risk Engines using Machine Learning Algorithms for unsecured credit products that will assess the credit risk of serious delinquency associated with a customer for a particular credit product.
• Built a Product Recommender Engine that models on the customers’ historic online behavior data to predict the customers that had the highest propensity to apply for a credit card.

Grandatos.com is a simple initiative driven by Escomm Group, aimed at delivering Analytics insights, hind-sights and fore-sights for everyday use for everybody.

As a Chief Data Scientist, my job role had me pitch, win and manage Analytics projects for multiple clients.

• Built targeted segments with personalized content for multiple campaigns with unique threshold CTRs and the overall conversions improved by 20%.
• Built a Marketing Response Model that predicts the conversion of potential customers by employing direct email marketing.
• Developed Twitter Analytics models which help understand Twitter followers, analyze competitors’ audience and follow #hashtag campaigns.
• Led the sales effort from Technical side by co-presenting sales pitches with customized data solutions and strategies.

IBM Global Business Services® is your business acceleration partner to co-create change and scale impact across your business. Work alongside our experts to reap benefits from connected processes, AI and automation, and a hybrid cloud architecture.

This was my first job after college. As a Software Engineer, I drove the effort in analyzing and reporting software quality for a Sales Automation tool built for AT&T.

• Appointed as the SPOC for all VoIP (Voice over Internet Protocol) related sales flow projects for both new and existing customers.
• Collaborated with SEs and Developers from multiple organizations, multiple cities and multiple time zones.
• Exceeded predicted targets for all projects and achieved recognition for having 0 red-flagged projects.
• Provided client training for Software Engineers on how to seamlessly transition from IBMers to IBMers partnering with AT&T.

Indian Institute of Management Calcutta (IIM Calcutta or IIM-C) is a top business school in Asia located in Joka, Kolkata, India. It was the first Indian Institute of Management to be established, and has been recognized as an Institute of National Importance by the Government of India in 2017.

During my time at IIM Calcutta I secured “Excellent” grade in 8 out of 12 modules. Courses:

• Financial Management
• Quantitative Analysis
• Operations Management
• Strategy Management
• International Business

College of Engineering, Guindy (CEG) is a public engineering college in Chennai, India and is Asia's oldest technical institution, founded in 1794. It is also the oldest technical institution to be established outside Europe.

During my time at CEG I secured a CGPA of 8.91/ 10. Courses:

• Probability and Statistics
• Operations Research
• Simulation Modeling and Analysis
• Advanced Optimization Algorithms
• Design and Analysis of Experiments