Acerca de Maximilià
- Adevinta (Kleinanzeigen): rebuilt CRM notifications data infrastructure across one of Europe's largest classifieds.
- United Nations (WFP / ShareTheMeal): built whole data landscape, A/B testing framework with 50+ experiments, propensity models in production at 85–96% accuracy, and ML for hunger forecasting.
- Zalando: 2 years across demand, pricing, warehouse and merchandising.
- Data foundations: modelling, governance, pipelines (AWS, Redshift, BigQuery, Databricks) and source-of-truth datasets.
- BI & reporting: Tableau dashboards designed around decisions, not vanity metrics.
- Experimentation: A/B testing frameworks from design to infrastructure.
- Machine learning: propensity, forecasting, segmentation, clustering. Deployed in production, not stuck in notebooks.
- Research & deep-dives: KPI driver analysis, customer behaviour, attribution, funnels.
- AI & automation: LLM-powered text structuring, RAG, internal assistants.
Inglés
Bilingüe o nativo
Español
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Italiano
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Catalán
Bilingüe o nativo
Francés
Competencia profesional básica
Portugués
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Alemán
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Experiencia
- Adevinta - KleinanzeigenFreelance Data ConsultantE-COMMERCEjulio de 2025 - diciembre de 2025 (5 meses)Barcelona, EspañaLed the end-to-end analytical definition of the CRM notifications domain (push, email, in-app) at Kleinanzeigen, one of Europe's largest classifieds platforms, taking the team from zero visibility to a complete understanding of the messaging funnel and user engagement.
- Designed the full data model: raw events, fact and model layers (sent → delivered → opened → session) and a behaviour-enriched mart layer; and defined the KPI framework, event taxonomy and naming conventions powering all downstream reporting.
- Performed extensive data discovery and exploration in Databricks: profiled event quality, audited inconsistencies across CRM systems and surfaced tracking gaps in the underlying database.
- Partnered closely with a data engineer on the production data model and with CRM engineering, Product and Design to co-define new events aligned with the analytical schema.
- Built Tableau dashboards covering the full notification funnel, KPIs and user engagement, iterating with business stakeholders to ensure clarity, usability and consistent visual language.
- Conducted deep-dive analyses on messaging logic, send timing and frequency, notification types, opt-in/opt-out behaviour and Notification Center usage, surfacing actionable insights for CRM optimisation.
- Translated complex analyses into clear narratives and stakeholder-facing decks, enabling data-driven decisions on CRM strategy and laying the foundation for future tracking and optimisation work.
- World Food Programme - UNData AnalystHIGH TECHnoviembre de 2021 - julio de 2025 (3 años y 8 meses)Berlin, GermanyLed the analytical development of ShareTheMeal and wfp.org for the United Nations World Food Programme (WFP), the world's largest humanitarian organisation fighting hunger and a 2020 Nobel Peace Prize laureate. Designed pipelines and analytical layers in AWS / Redshift, productionised ML models and LLM applications in Python, and built Tableau dashboards to enhance decision-making across Marketing, Product, CRM, Finance, Content and Management.
- Built the end-to-end reporting layer for ShareTheMeal across all business verticals (Marketing, Product, CRM, Finance, Content, Management), establishing a single analytical foundation for the organisation.
- Designed and ran a complete A/B testing framework enabling 50+ experiments, driving measurable improvements in conversion and retention.
- Developed and deployed propensity and revenue projection models (85–96% accuracy) integrated into CRM campaigns and business dashboards (+12% upsell increase), plus market-clustering models segmenting countries to tailor in-app prompts and messaging (avg. +6% conversion).
- Ran regression models to forecast critical hunger metrics across three countries, providing leadership with data-driven foresight for resource allocation.
- Consolidated multi-platform attribution data into a single source of truth, integrating feeds from multiple ad platforms and Adjust, and engineered an alternative iOS attribution pipeline working around SKAdNetwork limitations.
- Structured raw BigQuery event data into a unified sessions table powering full-funnel visibility of onsite user behaviour across web and app.
- Implemented automated text-structuring flows using LLMs, turning customer support chats, reviews and survey responses into actionable insights.
- ZalandoData AnalystE-COMMERCEoctubre de 2019 - noviembre de 2021 (2 años y 1 mes)Berlin, GermanyJoined Zalando, Europe's leading online fashion and lifestyle retailer, through a one-year rotational programme across Demand, Product, Warehouse and Pricing, before moving permanently into the Sales & Markets team at Zalando Lounge, the group's flash-sales platform for off-season fashion.
- Built the stock source-of-truth for Zalando Lounge: designed AWS/Redshift pipelines consolidating fragmented stock feeds into a single reliable view used across merchandising and operations.
- Designed an offer vs. demand ML score combining product-type and user conversion rates against available stock, helping merchandisers decide weekly assortment and balance returns.
- Developed campaign performance dashboards for merchandisers (brands, themes, weekly cadence), partnering with stakeholders to align on KPIs and reporting needs.
- Conducted deep-dive analyses on country and customer-cluster behaviour, online user journeys (funnels, session times) in BigQuery, and quantified category contribution and the impact of delivery delays on cancellations through regression modelling.
- Performed warehouse operational analysis profiling processing times and volumes by station, market and brand.
- Prototyped a dynamic discount-rate model in Pricing aimed at optimising weekly revenue margin.
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Formación
- Data Science DiplomaUbiqum Code Academy2019Data Science Diploma
- MSc in Renewable EnergiesUniversidad Autónoma de Madrid2013MSc in Renewable Energies