Description

I help brands understand which marketing investments are truly driving incremental revenue, measure channel-level ROI, and make smarter budget decisions.

I am an AI Marketing Scientist and Marketing Measurement Consultant with 4+ years of experience across Marketing Mix Modeling, incrementality, econometrics, revenue analytics, and data science. At NielsenIQ, I support end-to-end analytics and MMM engagements for global FMCG, consumer, beauty, and healthcare brands across international markets.

My work covers the complete measurement journey: business understanding, data specification, data preparation, EDA, model development, validation, decomposition, ROI/ROAS analysis, response curves, budget optimization, and executive-ready recommendations.

My core expertise includes:

• Marketing Mix Modeling

• Bayesian and regression-based MMM

• Incrementality and causal measurement

• Media contribution and revenue attribution

• ROI, ROAS, and marginal return analysis

• Budget optimization and scenario planning

• Model diagnostics and independent MMM review

• Python automation, dashboards, and data-quality workflows

I work across Search, Social, Video, Display, TV, OOH, Print, Retail Media, Affiliates, promotions, pricing, distribution, seasonality, and market controls.

My technical toolkit includes Python, SQL, Google Meridian, PyMC, pandas, statsmodels, Power BI, Streamlit, time-series analysis, adstock, saturation curves, and statistical testing.

Clients work with me when they need clear answers to questions such as: Which channels are generating incremental revenue? Where are we overinvesting or underinvesting? How should the next budget be allocated? Are our current MMM or attribution results reliable?

I am available for remote international projects, including complete MMM engagements, specialist modeling support, model audits, and ongoing marketing measurement consulting.

Langues

Anglais
Bilingue ou natif

Préférences en matière de lieu de travail

En télétravail uniquement

Travaille majoritairement à distance

NielsenIQ,
Analyst - MMM & Marketing Analytics Consulting
juillet 2025 - Aujourd'hui (1 an et 1 mois)
Vadodara, Gujarat, India
• • Develop and validate end-to-end Marketing Mix Models for global FMCG, beauty, and healthcare brands, including P&G, Ferrero, L'Oréal, Abbott, and Vanish, across TV, Search, Social, Display, Video, OOH, Print, pricing, promotion, and distribution drivers.
• • Own the modeling workflow from business requirement gathering and data specification through data processing, EDA, transformation, model development, scientific validation, decomposition, optimization, and stakeholder delivery.
• • Build additive, multiplicative, log-log/log-linear, and Bayesian regression models in Python using adstock/carryover, lag structures, saturation curves, trend, seasonality, holidays, promotions, and market controls to estimate short- and long-term impact.
• • Evaluate model validity using R-squared, MAPE, Durbin-Watson, residual diagnostics, coefficient significance, VIF/correlation, contribution plausibility, model stability, and business consistency checks.
• • Quantify baseline sales, incremental media contribution, ROI/ROAS, marginal returns, and response curves; translate findings into media budget scenarios and recommendations on over- and under-invested channels.
• • Design and evaluate geo-split, holdout, and A/B experiments to measure incremental sales lift, confidence intervals, and channel level causal impact, and use results to strengthen MMM validation.
• • Create reusable Python workflows, quality checks, analytical trackers, and stakeholder-ready outputs that improve repeatability, model governance, and delivery quality.
• • Present consulting-style recommendations to senior stakeholders across China, Denmark, Poland, India, and other markets, collaborating with marketing, sales, data engineering, operations, and product teams.
Marketing Mix Modeling Python Econometrics Bayesian Statistics
NielsenIQ,
Data Operations Analyst - Analytics, Data Quality & Automation
mars 2022 - juin 2025 (3 ans et 3 mois)
Vadodara, Gujarat, India
• • Managed analytics and data operations deliverables for global FMCG clients across the US, UK, Canada, Australia, and Europe, ensuring accurate, validated, and on-time datasets for reporting and decision-making.
• • Transformed high-volume product, customer, reference, and operational data into standardized analytical datasets through cleaning, mapping, fuzzy matching, classification, exception handling, and automated quality controls.
• • Built Python automation workflows that saved 80+ hours per month and approximately 1 FTE of manual effort, while improving consistency, traceability, and turnaround time.
• • Developed Power BI and Streamlit dashboards for operational KPIs, data-quality monitoring, workload tracking, variance analysis, and weekly/monthly business reviews.
• • Applied regression, clustering, factor analysis, significance testing, and root-cause analysis to explain anomalies, identify patterns, and support process and business decisions.
BYJU'S,
Business Development Associate
octobre 2021 - décembre 2021 (2 mois)
Ahmedabad, Gujarat, India
• • Exceeded sales targets by 120% and improved lead conversion by 15% by using SQL Server and Power BI to identify high-intent customer segments and prioritize outreach.