À propos de Samuel
AI Engineer | Data Scientist | Digital Ads Specialist
I help companies automate smarter, sell faster, and grow bigger — powered by AI & data.
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💼 What I do:
I build custom AI bots, automate repetitive workflows, and optimize digital ad campaigns to generate leads, save time, and drive revenue.
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📊 Real Results:
• 💸 Managed €400,000+ in ad spend across Google, Facebook, LinkedIn & TikTok
👉 Delivered +1.4M€ in revenue, reduced CPL by 30%, boosted lead quality across all funnels
• 🤖 Built 15+ custom GPT-powered bots (sales, legal, HR, customer support, LinkedIn automation)
👉 Examples:
• Legal AI bot processing 5,000+ docs/month → saved 40% review time
• LinkedIn bot generating 100+ qualified meetings/month
• Multilingual support bot with 90%+ accuracy in real-time replies
• 📈 Deployed predictive models for lead scoring, customer segmentation, and campaign optimization
👉 Clients saved 2,500+ hours/year and cut human error by over 80%
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🧰 Tools I Master:
Python, OpenAI (GPT-4), LangChain, Zapier, Make, SQL, Meta Ads, Google Ads, LinkedIn Ads, TikTok Ads, Notion API, Pinecone, Power BI, Streamlit, FastAPI
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✅ Let’s turn your business into an AI-augmented machine.
Whether you’re a startup, agency, or SME — I’ll bring the automation and performance your team is missing.
Français
Bilingue ou natif
Hébreu
Bilingue ou natif
Anglais
Bilingue ou natif
En télétravail uniquement
Travaille majoritairement à distance
Expériences
- LeoData scientistBTP & CONSTRUCTIONjanvier 2023 - février 2024 (1 an et 1 mois)Paris, FranceRole: Data Scientist – Leo (Energy Renovation Sector)At Leo, a company specialized in energy-efficient home renovations, I worked as a data scientist for one year with a mission to turn operational data into actionable insights for sales and strategic growth.🔍 Key Responsibilities• Lead Conversion Prediction:Developed scoring models to predict the conversion likelihood of incoming leads using behavioral data (response time, call history, lead source).👉 Result: +27% increase in conversion rates for the sales team.• Advanced Customer Segmentation:Used clustering techniques (K-Means, DBSCAN) to identify key customer profiles based on location, motivation (ecological vs economic), and buying behavior.👉 Enabled targeted marketing campaigns with higher ROI.• Ad Campaign Optimization:Built dashboards and recommendation models to guide the marketing team on which acquisition channels (Facebook Ads, Google Ads, etc.) to prioritize.👉 Achieved a 30% reduction in cost per lead within 3 months.• Automated Performance Reporting:Automated weekly performance reports for management and field teams using Python, SQL, and Power BI — tracking KPIs, delays, anomalies, and lead progress.• Strategic Decision Support:Delivered actionable insights for project prioritization, installer evaluation, and fraud detection across customer and lead databases.🧰 Tech Stack• Python (Pandas, Scikit-learn, XGBoost)• SQL (BigQuery & PostgreSQL)• Power BI / Tableau• Zapier & Notion for internal process automation
- SV DATA CONSULTINGDigital MarketingE-COMMERCEjanvier 2019 - Aujourd'hui (7 ans et 5 mois)Paris, FranceAs a freelance consultant, I worked with companies in the energy renovation, e-commerce, and B2B services sectors. I combined data science expertise with high-performance digital advertising strategies, managing over €400,000 in advertising spend across multiple platforms.⸻📣 Digital Marketing Achievements• Managed large-scale ad budgets:Oversaw and optimized campaigns across:• Google Ads: €150,000 spent → average CPL reduced from €52 to €34• Facebook Ads (Meta): €180,000 spent → +45% increase in qualified leads• LinkedIn Ads: €40,000 spent → targeting B2B decision-makers with +300% ROAS in niche sectors• TikTok Ads: €35,000 spent → low-cost awareness campaigns with < €0.03 per view• ROI-Focused Strategy:Developed and executed funnel-based strategies (TOFU–MOFU–BOFU), combining creative testing, behavioral segmentation, and retargeting.👉 Delivered up to €1.2M in revenue generated across all client portfolios in less than 12 months.• Landing page & CRO optimization:Used heatmaps, A/B tests, and scroll-depth analysis to boost page performance.👉 Achieved a +23% lift in landing page conversion rate.
- GoogleData Scientistjanvier 2022 - janvier 2023 (1 an)Led the redesign of core ranking algorithms for Google Search, improving click-through rates (CTR) by +12.6% across key verticals (News, Shopping).Developed and deployed a BERT-based classification model to better interpret ambiguous queries, reducing user bounce rate by -9.3% in A/B testing.Collaborated with the Ads team to implement real-time bidding optimization, increasing ad revenue by $37M/year through better prediction of user intent.Created automated pipelines using TensorFlow, BigQuery, and Airflow, reducing model deployment time from 3 weeks to under 5 days.Conducted extensive causal inference analyses to measure the impact of UI changes on user behavior using DoWhy and Google CausalImpact.Mentored 4 junior data scientists and collaborated with cross-functional teams including UX researchers, software engineers, and product managers.Presented findings to senior leadership, influencing roadmap prioritization for Search Intelligence in EMEA region.
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Formations
- Ingenieur Data SciencePolytechnique2022Specialization: Applied Mathematics and Computer Science Graduated: 2022 Rigorous multidisciplinary training in mathematics, physics, and computer science, complemented by courses in economics and innovation. Completed competitive coursework in machine learning, statistics, algorithm design, and data analysis. Conducted a 6-month research internship on optimization techniques for large-scale machine learning models. Member of the Data Science student club; participated in multiple hackathons and industry case studies. Ranked in the top 10% of the program (if applicable).