I help brands measure what is actually driving sales using Marketing Mix Modeling, ROAS analysis, dashboards, and growth analytics. Also supporting big firm for certification If you are spending money on marketing but are not fully sure which channels are actually driving sales, I can help you find the answer with data. I am a Data Scientist and Marketing Analytics Specialist with 4+ years of experience working on Marketing Mix Modeling, growth analytics, ROI measurement, ROAS analysis, media contribution analysis, statistical modeling, dashboards, and automation for FMCG and consumer brands across markets such as the US, UK, Canada, Australia, Europe, and Asia. I have worked with NielsenIQ and supported marketing and analytics projects for major brands other large FMCG and consumer businesses. I have also worked with international clients, including a South Korean client, where I built AI-driven dashboards, marketing analytics systems, and automation workflows to support business and marketing decisions. My main focus is helping brands answer important growth questions such as: 1. Which marketing channels are truly driving incremental sales? 2. How much revenue is coming from TV, Meta, Google, YouTube, Search, Display, Retail Media, Promotions, or other channels? 3. What is the real ROI / ROAS of each marketing channel? 4. Where is the budget being wasted? 5. How should the media budget be reallocated to maximize sales, revenue, or profit? 6. What happens if we increase or decrease spend on a specific channel? 7. Which campaigns are saturated and which still have room to scale? 8. How can marketing, sales, pricing, promotions, seasonality, and external factors be measured together? What I can help you with: Marketing Mix Modeling / MMM - Build MMM models to measure media contribution and incremental sales - Apply adstock, decay, lag effect, and saturation curves - Estimate baseline sales vs marketing-driven sales - Calculate channel-level ROI, ROAS, CPA, and marginal ROI - Measure the impact of TV, digital, paid social, search, display, promotions, pricing, and seasonality - Create budget optimization and scenario planning models - Show what happens when media spend increases or decreases Growth Analytics & Marketing Performance - Analyze campaign performance across paid and organic channels - Identify high-performing and underperforming marketing channels - Build clear KPI frameworks for marketing teams - Connect marketing activity to sales, revenue, and business outcomes - Find patterns in customer behavior, sales trends, and campaign performance Dashboards & Reporting - Build automated dashboards in Power BI, Looker Studio, Excel, or Google Sheets - Create executive-level dashboards that are simple and decision-focused - Track ROAS, ROI, spend, sales, revenue, contribution, conversions, and growth KPIs - Turn messy marketing reports into clean, easy-to-understand insights Data Cleaning & Automation - Clean and structure messy sales, media, campaign, and business datasets - Automate recurring reports using Python, Excel, Google Sheets, or dashboards - Build repeatable workflows so teams do not waste time on manual reporting - Combine multiple data sources into one reliable reporting system Tools and skills I work with: Python, Pandas, NumPy, Scikit-learn, Statsmodels, Excel, Google Sheets, Power BI, Looker Studio, SQL, marketing analytics, statistical modeling, regression analysis, data visualization, automation, MMM, ROAS analysis, ROI measurement, and growth analytics. My approach is simple: First, I understand the business problem. Then, I clean and structure the data. After that, I build the right model or dashboard. Finally, I translate the results into clear business recommendations. I do not just deliver charts or technical outputs. I focus on answering the real business question behind the data: “What should we do next?” If you need help understanding marketing effectiveness, measuring ROI, improving ROAS, optimizing media spend, building dashboards, or turning complex data into practical growth decisions, I would be happy to help.

🚀 Marketing & Brand Strategy Expert | Fractional CMO | Top 1% Upwork Freelancer 🌟 Top 1% Expert-Vetted Freelancer | PhD in Marketing, Analytics & Strategy | 100% Success Rate🌟 Specialist in healthcare, B2B & premium DTC 💡 About Me:Fractional CMO and senior marketing strategist with 25+ years of experience and a PhD in Marketing, specializing in analytics, statistics, consumer behavior, brand strategy, go-to-market planning, and Marketing Mix Modeling (MMM). I help companies make smarter marketing decisions through Marketing Mix Modeling (MMM), rigorous analytics, and senior-level fractional CMO leadership — combining executive strategy with the kind of data discipline most marketing consultants cannot offer. My work combines executive-level strategy with rigorous analysis. I do not just recommend tactics. I help clients determine what is working, what is not, where the next dollar should go, and how to build a more scalable and accountable marketing system. 📊 My strengths include marketing strategy, brand positioning, market research, customer insight, conversion analysis, go-to-market planning, and Marketing Mix Modeling (MMM). I am especially strong when a company has meaningful potential but needs clearer direction, stronger prioritization, tighter execution, or more analytical decision-making. Over the course of 25+ years, I have worked across healthcare, B2B, premium DTC, and complex growth environments where messaging, performance, customer insight, and budget allocation all need to work together. Clients bring me in when they need senior-level strategic thinking backed by real data, not guesswork. What I Help Clients Do 🚀 Fractional CMO Leadership Strategic direction, growth planning, team oversight, channel prioritization, and executive-level decision support 📈 Marketing Strategy & Go-to-Market Planning Growth strategy, launch planning, audience targeting, competitive positioning, and full-funnel planning 🧠 Brand Positioning & Messaging Clearer differentiation, stronger messaging, sharper offers, and more effective brand architecture 📊 Analytics, MMM & Marketing Efficiency Marketing Mix Modeling, media mix attribution, KPI development, budget allocation, forecasting, performance analysis, and decision support 🔍 Market Research & Customer Insight Segmentation, customer interviews, competitive analysis, survey design, and insight development 💰 Paid Media Oversight & Funnel Improvement Channel strategy, conversion analysis, ad performance review, and identifying where spend is being wasted Selected Accomplishments 🏆 Analytics & Performance Built MMM frameworks that reduced ad spend by 35% while maintaining or improving revenue performance Improved ROI by 96%+ through tighter funnel analysis, better conversion tracking, and stronger message-market fit Lowered cost-per-sale by 10x and reduced spend-per-unit by 300% through performance-based campaign restructuring Managed high-7-figure ad budgets across Google, Meta, Amazon, and LinkedIn with measurable efficiency gains Built MMM and predictive forecasting models to optimize budget allocation and eliminate wasted spend across multi-channel programs 🏆 Strategy & Positioning Developed brand positioning and messaging strategies that improved conversion, clarity, and differentiation Led go-to-market planning and rebranding for businesses at inflection points, resulting in measurable gains in engagement and acquisition efficiency Built audience segmentation models that reduced CPA and improved targeting precision across paid channels Designed competitive positioning frameworks that sharpened market entry and accelerated growth 🏆 Executive-Level Marketing Leadership Served as a strategic marketing leader for healthcare, B2B, & premium consumer brands Helped founders and leadership teams prioritize the right channels, investments, and growth opportunities Brought analytical rigor to decisions that were previously based on assumptions or fragmented reporting Why Clients Hire Me 🔥 25+ years of marketing experience across strategy, analytics, positioning, and growth 🔥 PhD-level expertise in marketing, statistics, and consumer behavior 🔥 Senior-level fractional CMO leadership, not just tactical execution 🔥 Deep specialization in MMM, media mix attribution, and data-driven budget optimization 🔥 Strong ability to connect brand, performance, analytics, and customer insight into one clear growth plan Tools & Platforms: GA4 · Google Ads · Meta Ads · LinkedIn Ads · Amazon Seller Central · Tableau · Looker · SPSS · HubSpot · Salesforce · Mailchimp · MMM Good Fit: Healthcare, B2B, premium DTC, funded startups, and established companies that want senior-level strategic marketing leadership with real analytical depth. Not a Fit: Paid survey projects, unfunded startups, or speculative industries. 📩 Need a fractional CMO with 25+ years of experience, a PhD in Marketing, and deep strength in MMM, attribution, analytics, & positioning? Let's talk.

Customer lifetime value (CLV/LTV) modeling is my specialty. Using probability models (BG/NBD, Pareto/NBD, Gamma-Gamma), retention curves, and RFM segmentation, I tell you who your most valuable customers are, what they are worth, and how to acquire more of them. Around that core I bring the full marketing-analytics toolkit - marketing mix modeling (MMM), multi-touch attribution, pricing, and forecasting - in Python and R, for CPG, DTC, media, fintech, and B2B clients. Over 30 years I have directed more than $70M in combined consumer-insights and analytics spend - $20M+ client-side (Bacardi Global Brands) and $50M+ agency-side (GfK, Millward Brown/Kantar) - so I read these models the way a CMO does, not just a data scientist. I translate model output into the decision, the deck, and the board-ready story. What I deliver: - Customer lifetime value (CLV/LTV): BG/NBD and Pareto/NBD + Gamma-Gamma probability models, retention curves, cohort and RFM segmentation; forecast customer value and surface your most valuable acquisition cohorts for DTC and subscription brands. - Marketing mix modeling & media ROI: ARIMAX, Bayesian/hierarchical, and regression models with adstock and saturation; in a recent engagement I identified a channel-reallocation opportunity worth roughly a 185% gain in marketing efficiency. Build from scratch, or finalize, validate, deploy, and maintain existing models (Python or R). - Attribution & measurement: reconciling Meta / Google / GA4 platform reporting against actual business outcomes; blended CAC and single-source-of-truth frameworks. - Pricing & forecasting: conjoint / willingness-to-pay studies and supervised-ML pricing models (random forest, gradient boosting) deployed as interactive calculators. - Data engineering & viz: BigQuery warehousing, dashboards (Power BI, Tableau, Looker Studio), and clear recommendations leadership can act on. Credentials: Wharton MBA (Marketing), Brown B.A. in Applied Mathematics. Top Rated on Upwork with 100% Job Success across 8 engagements. Stack: Python, R, SQL, SAS, Azure, AWS, GCP/BigQuery, Power BI, Tableau, GA4, Looker Studio. Fluent in Spanish, working Portuguese - comfortable on global, multi-market engagements. I keep scope tight, communicate in business terms, and hit deadlines.

I help organizations transform complex data into actionable insights that drive growth, improve decision making, and create measurable business value. With a PhD in econometrics, statistics, and causal inference and more than a decade of quantitative experience, I specialize in data science, predictive modeling, survey research, marketing analytics, business intelligence, experimentation, and advanced statistical analysis. My experience spans e-commerce, iGaming, insurance, banking, non-profit, automotive, telecom, retail, healthcare, engineering, and research sectors. I have delivered projects ranging from forecasting, predictive modeling, customer analytics, and large-scale survey research to marketing measurement, attribution, and end-to-end analytics platforms. I have extensive experience working with survey and observational data, including questionnaire design support, survey data cleaning and validation, scale and index construction, missing data handling, exploratory analysis, statistical modeling, and results visualization. I have analyzed customer, employee, stakeholder, healthcare, and research survey data using techniques such as logistic regression, count models, multilevel models, Bayesian methods, and causal inference approaches, translating complex findings into actionable recommendations. I have extensive experience building data-driven solutions using Python and SQL, including data analysis, machine learning, forecasting, statistical modeling, Bayesian analysis, survey analytics, customer segmentation, and decision-support systems. My expertise includes Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), incrementality measurement, A/B testing, geo experiments, brand lift studies, causal inference, and Bayesian methods. Experienced in developing Bayesian MMMs using PyMC-Marketing and Google Meridian, I help organizations understand the true drivers of business performance by quantifying channel contribution, adstock and saturation effects, ROI, and budget optimization opportunities. I translate complex analytical findings into practical recommendations that stakeholders can confidently act upon. I have worked extensively with data from Google Ads, Meta, TikTok, LinkedIn, CRM systems, call-tracking platforms, survey platforms, web analytics tools, customer databases, and cloud data warehouses. My technical background includes HubSpot, Datacor, BigQuery, GA4, Snowflake, and custom internal data sources, with a strong focus on data integration, validation, ETL processes, and scalable analytics workflows. Beyond analysis and modeling, I develop dashboards, visualizations, and decision-support applications using Streamlit, Looker, Plotly, and business intelligence platforms. I am passionate about making data accessible and useful, whether through executive dashboards, interactive analytics applications, or clear communication of complex statistical results. I also have extensive experience teaching, mentoring, and collaborating with technical and non-technical stakeholders. As a former university professor, I designed and taught graduate-level courses in statistics, econometrics, quantitative methods, and research design. Whether supporting business leaders, training analysts, or working with cross-functional teams, I focus on delivering solutions that combine analytical rigor with practical business impact. Whether the goal is building predictive models, improving reporting infrastructure, analyzing survey data, conducting statistical research, optimizing marketing investments, measuring incrementality, forecasting business outcomes, or developing advanced analytical solutions, I bring a rigorous quantitative approach and a proven track record of turning data into decisions.

I help growth, SaaS, eCommerce, and healthcare teams measure channel contribution, estimate ROI/mROAS, and allocate marketing budget using Bayesian MMM, attribution analysis, forecasting, and executive-ready dashboards. If you are investing in Meta Ads, Google Ads, GA4, Shopify, CRM, or call-tracking data but still lack clarity on what is actually driving revenue, leads, qualified calls, or bookings, I can help you turn that data into business decisions. I work with companies that want more than basic dashboards. I build decision-ready models, analyses, and reports that help answer questions such as: • Which channels are truly driving revenue, qualified leads, or booked appointments? • Where is marketing budget being wasted? • What is the estimated ROI and marginal ROI by channel? • Where are channels approaching saturation? • How should marketing spend be allocated more efficiently? • What risks, assumptions, and limitations should decision-makers understand before acting? My core expertise includes: • Bayesian Marketing Mix Modeling • ROAS, mROAS, and ad spend analysis • Marketing attribution and incrementality thinking • Budget allocation and saturation analysis • Revenue, lead, and demand forecasting • Channel contribution analysis • LTV, CAC, cohort, and funnel analysis • Customer segmentation and retention analysis • Executive dashboards and decision-ready reporting For MMM and marketing measurement projects, I focus on practical business interpretation, not just model output. A good model should make assumptions explicit, show uncertainty, avoid unrealistic ROI claims, and translate results into clear budget recommendations. Tools I work with: Python, SQL, PyMC / PyMC-Marketing-ready workflows, GA4, Shopify, Google Ads, Meta Ads, BigQuery, Tableau, Looker Studio, Power BI, Excel What clients can expect from working with me: • Clear and structured analysis • Actionable recommendations, not just charts • Business-focused insights tied to growth and profitability • Clean dashboards and executive-ready reporting • Transparent assumptions, limitations, and model interpretation • A reliable partner who understands both data and marketing decisions I combine technical depth, marketing understanding, and business thinking to help companies make better decisions, reduce wasted spend, and grow more efficiently. If you need help with marketing measurement, Bayesian MMM, attribution, forecasting, customer insights, or performance dashboards, I can support your project.

Marketing Analyst with a Bachelor's in Business Analytics and Marketing, specializing in Performance Analysis (MTA, MMM, machine learning, causal inference) to support decision regarding ROAS, CAC, and LTV optimization with fluent English and a vibrant energy ^^ My expertise centers around Marketing Mix Modeling (MMM), including Robyn-based solutions for social media and overall marketing optimization, alongside causal inference, Multi-Touch Attribution (MTA) strategies to fully understand campaign impact. With a solid foundation in Data Science, causal inference, Machine Learning, and Marketing, I transform raw data into useful insights. I cut through fragmented information and attribution chaos to truly optimize your ROAS and LTV:CAC for sustainable growth. - In terms of programming languages, I use Python and R for advanced statistics, data analysis, and MMM - For dataset organization, I leverage DAX, Excel, and Google Sheets. - When it comes to database management and queries, SQL and SSMS are my go-to tools. - And for powerful Data Visualization, you'll find me using PowerBI, Looker Studio, and Tableau. Do you have another tool in your stack? I will be more than happy to have a look and integrate! Communication is key! I am fluent in English, Arabic, and French, with basic knowledge of German. In terms of team collaboration? Well, with over 4 years of experience in international work settings, I'll fit into your team just like a missing puzzle piece. What's left to say? Let me know, and I will be more than happy to help you make the most out of your marketing data.

PROFILE Results-oriented leader with expertise in strategic project planning and ROI, executional strategies and tactics. Experience in marketing mix analysis, forecasting, category management, sales analysis, trade marketing, consumer and shopper insights, analytics, new product development, brand strategy and project management.

Most companies can measure what happened. Very few can prove why — or quantify what it was worth. That's the gap I've spent 20 years closing. I'm a senior analytics and AI advisor who builds the frameworks that connect marketing, communications, and business investment to measurable outcomes. I've done this work for LEGO, Target, Nestlé, PepsiCo, IKEA, and dozens of others — at Accenture, Meta, A&MPLIFY, and Edelman — across marketing mix modeling, causal inference, econometrics, attribution, forecasting, and AI-enabled measurement systems. What I bring to freelance engagements: Marketing Mix Modeling (MMM) — building and interpreting models that quantify what's actually driving revenue across paid, earned, and owned channels Causal Inference & Incrementality — going beyond correlation to prove what caused an outcome and what would have happened without a given investment AI-Enabled Measurement — designing measurement systems that incorporate LLMs, predictive modeling, and automated insight generation Executive Translation — taking complex analytical findings and turning them into clear strategic recommendations for C-suite decision-makers Analytics Strategy — assessing measurement maturity, identifying gaps, and building roadmaps for organizations that want to make better decisions with data I work best with clients who have a hard measurement problem, a strategic decision that needs analytical grounding, or a measurement function that needs a senior outside perspective. Engagements range from focused model builds to ongoing advisory.

5+ years experience in data analysis & data science, with focus on marketing & product. Worked on projects that range from daily reporting & monitoring, causal inference (A/B testing/ geographic experimentation/synthetic control/marketing mix modeling) and machine learning & data mining (churn prediction/customer segmentation/basket analysis). Currently mostly working on projects in the marketing science domain. Consulted other departments for statistical projects and helped C-level executives with data-based decision making using presentations, written reports and meetings. Tech stack: Python, SQL, Git

🎖️ Tell me where your marketing budget goes, and I'll show you which part actually works and where the next dollar should go. That is the whole job, and it is what I have done for the last 8+ years. Most teams are measuring marketing by guessing. Last-click takes the credit, the platforms mark their own homework, and nobody can say what a channel is truly worth. I fix that with proper marketing measurement: Marketing Mix Modeling, multi-touch attribution, and incrementality testing that tells you what is causing sales, not just what is correlated with them. I work with founders, growth leads, CMOs and marketing teams who spend real money on paid media and want to trust their numbers before they scale them. What I build: - Marketing Mix Models (MMM), hierarchical Bayesian, to measure each channel's true contribution and reallocate budget; - Multi-touch attribution (Markov chains, Shapley value) across messy, non-linear customer journeys; - Incrementality and causal inference: geo-lift, geo-holdout, difference-in-differences, synthetic control, A/B and experimentation programmes; - Predictive models: churn, LTV, lead scoring, propensity, next best action; - The analytics stack underneath it all: GA4, Google Tag Manager, BigQuery, Snowflake, dbt, Looker dashboards. A few results from past work: - 1.5M EUR unlocked through MMM-driven budget reallocation; - 5M EUR+ in incremental revenue from a structured A/B testing and experimentation roadmap; - 32% lift in projected lead value by moving paid acquisition to value-based bidding; - 27% lower CPA and 15% higher conversion rate through better measurement and targeting. How I work: I treat marketing measurement as causal. I never trust a single model, so I triangulate MMM against attribution and incrementality experiments to make sure the numbers are real. And I translate all of it into one clear recommendation a non-technical founder can act on, because a model nobody uses is worthless. You are a strong fit if: - You spend on paid media (Google Ads, Meta, TikTok) and cannot prove what is working; - You need MMM, attribution, or incrementality testing done properly; - You have data but no clear path from data to decision; - You want senior judgement, not a junior running a template. Not a fit if: - You want last-click attribution to keep telling you what you want to hear; - You are looking for the cheapest possible setup over a correct one My stack: Python (pandas, scikit-learn, PyMC), R, SQL, BigQuery, Snowflake, dbt, Vertex AI, Looker, GA4, Google Tag Manager, Google Ads, Meta Ads. I am a PhD candidate in Data Science at NOVA-IMS researching causal inference, so you get academic rigour combined with in-house growth-team pragmatism. Expertise: Marketing Mix Modeling, MMM, Media Mix Modeling, Marketing Measurement, Multi-Touch Attribution, Attribution Modeling, Incrementality Testing, Geo-Lift, Causal Inference, Bayesian Statistics, Marketing Analytics, Predictive Modeling, Churn Prediction, Customer Lifetime Value, LTV, Propensity Modeling, A/B Testing, Experimentation, GA4, Google Tag Manager, Conversion Tracking, BigQuery, Python, Data Science. Send me a brief and I will reply within a few hours.