Ashwin Pai Email & Phone Number

San Jose, CA, US

New York, US

Working on blending data engineering and data science to solve high impact problems at scale!

Columbia, MD, US

• Managing delivery across data science and data engineering teams focused on the High Tech industry in the Bay Area, responsible for P&L of $2M
• Drivers of product adoption, multi-surface/channel/platform/ad-set optimization to improve engagement for young audience-focused content creators - improved targeting efficiency with 25% reduction in CPM, increased.
• Built frameworks for channel optimization and sequencing to maximize content through Media Mix & Attribution Modeling
• Worked on quantifying links between user sentiment and incremental content production, defined pathways to optimize this halo relationship for key target cohorts
• Consulted with CX teams, identified gaps in the customer journey and recommended actions to improve post-purchase NPS of flagship VR headset

Mumbai, Maharashtra, IN

• Managing delivery, resourcing and client success for a large part of 'Audience Analytics' portfolio (>$1M annual topline) with >30 team members delivering advanced data-driven Marketing solutions across Retail, BFSI.
• Optimized marketing and attribution across multiple channels for substitute drugs to recoup revenue loss from global Pharma client's blockbuster drug becoming generic; potential saving estimated to be over $30M
• Market mix and inter-channel synergy modeling for a large technology client – working towards optimal budget allocation across media channels to lift brand awareness (with weighted message pull-through as outcome metric)

Mumbai, Maharashtra, IN

• Managed P&L, delivery and growth for >$1M portfolio with multiple team/projects
• Played key roles in critical talent hiring, training and scaling delivery post Merkle acquisition
• Market mix modeling for a global cosmetics brand: modeled for sales attribution from various media channels using multiple regression techniques – resulted in optimized budget allocation of $20M with an estimated ROI.
• Customer and digital marketing analytics for a North American omnichannel retailer: insights on customer journeys, loyalty behavior, competition sensitivity and digital media campaign effectiveness helped in doubling.
• Financial modeling for loyalty programs: Incrementality & cost drivers, tier shift simulations and sensitivity analyses o EMEA focused cosmetics retailer’s rewards program revamp: est. bottom line improvement of €0.7Mo.
• Product Analytics for major secondary ticketing marketplace’s International (APAC/LATAM/EMEA) business: o Advanced conversion funnel breakdowns and analyses for multi-device interactions using Google Analytics and.

Mumbai, Maharashtra, IN

• Dynamic stock buffering to reduce out-of-stock resulting in cross-channel fulfillment levels (units DIF) of 98%
• Played a key role in negotiating multi-million dollar freight deals with 3PLs, data-driven strategies and simulations resulted in savings of > 10M AUD
• Co-ordinated the application/integration of Ugam’s in-house ML suite for automated content writing / OCR / attribute extraction from text and images in the client’s content workflow; ~30% productivity increase observed

Mumbai, Maharashtra, IN

• Streamlined online SKU onboarding process involving hundreds of suppliers across APAC – resulted in reducing stage-wise TAT and thousands of dollars in savings by identifying & quantifying gaps in the supply chain
• Helped the fulfilment team in unravelling freight loss across their complex ANZ network involving 3PLs and >100 stores – analyses on freight processes, store operations, consumables usage, etc. enabled >$1.2M savings.
• Topic modelling (LDA) to mine customer pain points in service center data from multiple sources (phone/web/social media) – actions taken from these insights resulted in improved FAQs and a 30% drop in inbound complaint.
• Product alternate identification for a large US B2B distributor using multiple unsupervised ML and string-matching algorithms – alternates generated for 80% of products across 35 key categories increased cross-selling.
• Listing productization mapping for an Australian e-commerce marketplace: increased product grouping coverage up to 60% (over existing 40%) using multiple unsupervised ML algorithms as part of assessing market.

Northbrook, IL, US

• Led 5-member team focused on building a ML powered tool for personalized targeting of millennials based on interests extracted using time-specific context of their tweets
• Named Entity Recognition + Semantic Role Labelling (NER-SRL) and Topic Modelling (LDA) for context mining/extraction
• ML techniques: logistic regression, k-NN & SVM for classification; k-means, DBSCAN and PAM used for clustering

Northbrook, IL, US

• Led 4-member team focused on continually improving effectiveness of marketing activities
• Segmentation of B2C customers using unsupervised ML (k-means) and developed a framework for segment x lifecycle specific personalized marketing campaigns
• Multivariate linear regression model to predict the next shopping window for customers - this formed the backbone of client’s contact strategy, generating >$8M AUD incremental sales annually

Northbrook, IL, US

• SKU level targeting for supplier funded campaigns: ensured seamless execution of multi-channel national, state and local (in-store and online) targeted campaigns
• Reward benefit validation: Modeled for activation, retention, uplift, halo benefit, etc. of popular rewards to customers of the retailer’s financial services – quantified incremental benefits leading to improved.
• Campaign Data Model (CDM) in Oracle SQL: part of team that built and maintained the model

Mumbai, Maharashtra, IN