Data Visualization Experts in Berlin

Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.

• Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
• Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
• Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
• Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
• BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.

I run my own freelance agency based in Berlin and help startups and teams.

• I helped 100+ businesses achieve the digital products they wanted.
• Took ownership of the design process, collaborating with other teams.
• Conducted design thinking, user research, and competitive analysis.
• Developed design concepts, wireframes, and high-fidelity prototypes.
• Optimized websites and their conversion rates to reach more clients.
• I help clients in tech, hospitality, luxury, real estate, and professional services.
• I work with long-term products and clients like Accor, Corso Da Vinci, Webwavers, and ImmoTrust.

• Detecting fraud patterns by implementing aggressive anti-fraud rules while maintaining acceptable false positive rates, reducing fraud exposure to users by up to 80%
• Supporting ideation and roll-out of new trust and safety features to block fraudulent activity and increase user awareness for fraud
• Supporting Product, Development and Customer Support with BI reports and further guidance to identify and fight fraud and policy violations

• Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
• Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
• Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
• Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
• Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow

• Leading coordination between business units and IT
• Coordinating development and testing
• Business analysis and structured requirements gathering
• Specifying functional and technical requirements
• Integrating interfaces to internal systems
• Developing SQL queries and reports
• Documentation in Confluence Result: On-time go-live, structured and agreed project basis, ensuring a coordinated project workflow.

• Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
• Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
• Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
• Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
• Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
• Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
• Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.

In a lean, execution-focused environment, I took ownership beyond a narrow engineering lane, shaping and implementing systems across backend, data, and infrastructure. Partnered directly with the three founders in a fast-moving, high-stakes environment, turning strategic priorities into concrete technical decisions and production outcomes.

• Owned core platform development across backend (Django/Rest Framework/Postgres), ETL (Python/Dagster), infrastructure (Terraform/Kubernetes/AWS), and frontend (typescript/react) for a climate-tech SaaS product, driving continuous cross-stack development across five repositories from October 2021 to this day.
• Architected and owned a standalone internal Python scoring framework for CRC assessments, using YAML-driven rules and metaprogramming to enable non-technical users to define complex evaluation logic without hardcoded implementations.
• Built and stabilized ETL and scraping pipelines using Dagster and Scrapfly, improving document ingestion, tagging, retry behavior, deployment flow, and operational resilience.
• Contributed to platform modernization and reliability through Django/Python upgrades, Postgres/RDS and EKS changes, CDN/TLS updates, test and performance improvements, and observability hardening.
• Drove backend engineering for product features, translating requirements into technical specifications, API contracts, data structures, and scalable implementation plans.

• Developing methods for monocular 3D facial reconstruction and personalized geometric modelling from mobile imagery
• Building learning-based approaches for facial shape estimation, video-based facial analysis, and privacy-preserving visual learning

• Managing and scaling multiple client accounts (Meta & Google Ads) with a focus on ROAS and CPA
• Developing and A/B testing ad creatives, offers, and landing pages
• Building email and flow automations in Klaviyo (welcome, abandoned cart, post-purchase)

• Rapidly operationalized measurement frameworks and insight generation to evaluate go-to-market initiatives, directly influencing regional planning and investment decisions within the first 60 days.
• Led complex attribution and incrementality analyses to quantify campaign impact, identifying key trends that drove improvements in user adoption and engagement.
• Partnered with product and marketing leadership to translate complex behavioral data into prioritized OKRs and clear strategic narratives.

• Establishing Identity & Directory Management as a new (split-off) team & product within the IAM cluster.
• Leading the “Identity & Directory Management” product (8 people) as Product Owner.
• Concept for ‘Digital Identities’, i.e. IDs with n users/accounts and strategy for a modernized product offering.
• Upgrading APIs, migrating to a containerized infrastructure, rolling out international markets & standardized solutions across the REWE enterprise group.
• Tech: OpenText™ (NetIQ) eDirectory & Identity Manager, LDAP, SAP HR/HCM, Docker/Kubernetes/Podman, REST APIs, Microsoft Active Directory & Entra ID, postgresDB, Keycloak, Ansible, Cyberark (PAM), Apache Kafka, Jira, Confluence, Miro.

• Elevated LLM output reliability by engineering domain-specific prompts and evaluation logic, improving reasoning consistency across production language model workflows.
• Designed advanced coding benchmarks and validated solutions to strengthen training and evaluation datasets, improving model performance on technical problem-solving tasks.
• Designed and implemented automated evaluation frameworks for technical reasoning tasks; optimized LLM output reliability by 15% through rigorous prompt engineering and rubric-based benchmarking.

• Own strategy and roadmap for the payment orchestration and risk intelligence products serving enterprise subscription customers.
• Conduct deep workflow discovery and user interviews to redesign onboarding experience, resulting in 5× funnel throughput and 70% reduction in manual steps.
• Define PRDs for scalable data pipelines, fraud signals, and automation logic, improving insight accuracy and speed of decision-making by 30%.
• Partner with engineering, data, design, and security to ship 15+ enterprise features with 100% successful release quality.
• Introduce risk analytics dashboards and performance KPIs, reducing investigation time by 40% and improving visibility across teams.
• Lead prioritization of new capabilities, tech debt, and security initiatives (PCI DSS, access controls, auditability).
• Lead development of ML-based fraud detection models (regression, decision trees) to identify high-risk transactions, reducing chargebacks by 20%.
• Design end-to-end analytics dashboards (Tableau, Redshift) to visualise global risk exposure, cutting onboarding SLA from 2.4 days to 3 minutes.
• Partner with engineering and data teams to deploy scalable payment risk frameworks, enhancing compliance visibility and decision speed.
• Mentor analysts and data scientists through agile sprint cycles, embedding a data-driven culture across risk operations.

• Developed AI-powered analytics tools for drought prediction using CMIP6 data.
• Integrated UAV and satellite imagery to optimize predictive models for drought resilience.
• Designed a Decision Support System (DSS) for integrated water resources management.
• Partnered with industry and research institutions to deliver environmental monitoring solutions.
• Managed international projects, aligning data science innovations with policy and business goals.