Data Analyst · Information Science
I'm Nandita — a data analyst with a background in information science, drawn to the numbers behind beauty, fashion and luxury tech. I care about the moment a dataset becomes a decision, and a decision becomes a look.
Style No. NR—2026
Composition
Care Instructions
Handles ambiguity well. Best paired with real problems. Wash with rigor, dry with curiosity.
The Approach
From AI-driven HR transformation to solar market expansion to skin-condition modelling for L'Oréal — the throughline is the same: read the signal, understand the context, translate it into something a business can act on.
Transforming raw, messy datasets into structured insight — the kind that supports a decision rather than just describing a trend.
Competitive benchmarking and go-to-market thinking across cleantech, HR tech, consumer and fashion — with a particular pull toward beauty and luxury.
Bridging technical execution with brand and business needs — from KPI frameworks to CRM strategy — so the analysis actually gets used.
Professional Experience
A year of commercial analytics across international markets — flagging what was underperforming and reporting it straight to senior leadership.
Innovative Intelligent Solutions LLC
Selected Work
Consulting, machine learning and analytics projects spanning business strategy, fashion, music and finance.
Competed in L'Oréal's AI hackathon to build a skin condition classification model using knowledge distillation and Green AI optimisation techniques. Achieved significant model compression with reduced CO₂ emissions while maintaining classification accuracy.
Designed an end-to-end AI integration roadmap for CEVA Santé Animale's HR department — ATS screening, chatbot onboarding and wellness monitoring. Proposed ReferBuddy.ai, an NLP referral hiring platform, with full budget modelling and EU AI Act-aligned compliance.
Developed a full commercial strategy for a flexible solar film startup entering South India's cleantech market — 5P marketing analysis, competitive benchmarking, sector opportunity mapping and FY25–26 revenue forecasts, backed by a SMART KPI framework and CRM roadmap.
Reconstructed deleted playlists from a mixed family account using a two-stage ML classification approach, predicting missing user and year labels from audio features and listening history — with full confidence scoring across 5 users and 7 years.
Extended the Task 1 model with advanced feature engineering and enhanced classification techniques, plus a full usage guide for reproducibility and detailed enhancement documentation across the analytical pipeline.
Built a personal finance tracking application that automates income and expense logging, categorisation and reporting — with visual summaries of spending patterns and automated budget alerts.
Let's Talk — Selectively
I'm looking for teams in beauty, fashion or luxury tech where data actually shapes the story — not just reports on it. If that's you, I'd like to hear from you.
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