R Experts in Munich

• Managed the successful overall Trial and Commercial deployment of OpenRAN technology and swap-out of legacy SRAN for 2 mobile network operators in Germany.
• End-to-End Project life cycle governance and coordination of multiple Workstream leads i.e. Operations, Performance, Site Solution Management, Design, SW Delivery, Integration & Implementation, OSS Tools, 3rd-party Resource Support.
• Project planning to cover major milestones by delivering roadmap alignment in compliance with the German Network Regulatory Agency (BNetzA), as a vendor.
• Provided pre/post-Sales support to the Accounts Team for RfP/RfQ submissions.

PMO & Project Organization Blueprint for Restructuring

Renewable Energy / Solar Equipment

Technologies / Methods: PMO setup, KPI tracking, project organization, Jira, Confluence

• Developed measures to improve management control during a restruct...

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Development High-Performance ad distribution via auction
• Holistic (multi-campaign & multi-channel) advertisement placement optimization
• Algorithmic optimization for NP-Hard/NP-e
• Multiple Knapsack Problem with constraints
• Online estimation of parameters in stochastic environments

Tools: Python, R, Kotlin, MILP/SAT/CP Solvers, Pytorch, Pandas, Docker

• Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
• Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
• Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
• Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.

• Development and maintenance of IT architectures with embedded Linux systems.
• Designing, implementing, and optimizing backend applications and script-based solutions.
• Analyzing and resolving issues, including troubleshooting and user support.
• Developing and implementing security concepts for cloud solutions.
• Administering networks (DHCP, DNS, NTP, VPN).
• Technologies: Linux, PowerShell, Bash, Python, Ansible, Kubernetes, GitLab CI.
• Methods: Kanban.

• Migration of existing data jobs from Cognos Data Manager to Tibco/IBI Datamigrator
• Migration data jobs parametrisation for dynamic runs
• Optimisation and cutting-back
• Regression tests
• Knowledge transfer and documentation

• It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
• GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
• Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
• CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
• Development of feature store and data synchronization between environments
• Data science: evaluation of different forecasting models, including CatBoost, Contextual Gamma and Random Forest; implementation of training pipelines using Kubeflow on Vertex AI; scaling and development of an event-driven interface using Kafka as a forecasting service; evaluation of MLFlow for model tracking and model registry
• Implementation of REST API using KeyCloak OAuth2 and OpenID (JWT)
• Monitoring: implementation of dashboards with Grafana, Prometheus, Mimir, Streamlit and Loki to monitor prediction metrics, GCP and Snowflake costs for pipelines, and system metrics
• Development of Copilot Agent Skills

• Developed and maintained 5 Power BI dashboards for pipeline tracking, forecasting, revenue-gap, quota-achievement, and deal-performance analysis.
• Delivered weekly, monthly, and quarterly reporting used by approximately 100 stakeholders across Sales, Finance, and Marketing.
• Built semantic data models and ETL workflows using Power Query, DAX, and SQL; integrated Salesforce, SharePoint, internal data warehouse, and Excel sources.
• Automated data ingestion, cleaning, transformation, format standardization, KPI calculations, dashboard refresh, and reporting preparation using Power Query, DAX, and Power BI, eliminating several hours of recurring manual data preparation and reporting work.
• Standardized KPI calculations and built interactive reports with row-level security, drill-through, and Waterfall analysis for business reviews and forecasting.

• Designed, developed, and configured scalable data applications aligned with business processes and technical requirements.
• Architected scalable, cost-effective data architectures leveraging Snowflake across AWS, Azure and GCP, integrating dbt for data transformation and modeling.
• Built and maintained robust ETL Data Pipelines, ensuring high data quality for seamless migration and cross-system integration.
• Demonstrated strong expertise in SQL & Python with extensive experience in data modeling, ETL/ELT pipeline development, and streaming data processing; proficient in Git-based version control, CI/CD practices, and testing frameworks, with solid knowledge of data quality, observability, cost optimization, security, and data governance principles.
• Led multiple data migration initiatives from SAP HANA to Snowflake using a modular dbt framework.
• Designed and maintained end-to-end data transformation workflows using dbt on Snowflake, implemented layered data models, optimized performance, and ensured high-quality data delivery for business intelligence and reporting.
• Managed development, QA, and production deployments through structured version control and release management using GitLab.
• Integrated and centralized data from multiple sources including relational databases, flat files, Excel, and large-scale systems into Snowflake.
• Applied strong expertise in Sales, Marketing, HR, and ERP data domains, developing and maintaining relevant KPIs and reporting solutions.
• Collaborated with cross-functional teams to deliver end-to-end data solutions on schedule through proactive issue resolution and effective coordination.
• Administered the Snowflake sandbox environment for Data Engineering division.
• Trained colleagues transitioning into data roles on Snowflake and provided technical guidance and mentorship to junior team members.

• AI vision development: Match external best practices with analysis of processes, interfaces, stakeholders, data flows, and output KPI, creating a long-term target picture of process automation and AI augmentation
• Curated employee training framework, e.g. for public service foundation: Basics of AI, generative AI applications, evaluation of human judgement and machine control in socially critical applications
• Implemented advanced upskilling courses specialized for product managers: Using AI in innovation, portfolio management, process automation, and marketing to promote novel products and services
• Multiple keynote speaker: AI-driven organizational transformation powered by cultural transformation and forward-looking leadership practices
• Ongoing exchange of expertise and experiences with personal network of leading AI strategists at multinational corporations, e.g., Siemens, Mercedes-Benz, BMW, McDonald’s, Adidas, Linde, Infineon, TÜV Süd, to collect business best practices
• Cooperation with expert leadership networks, e.g. TEC Leadership Institute and PM1 to strengthen impact through increased reach across organizations and industries

Led end-to-end recruitment

• I began my career at the National Statistics Office as an Assistant Expert and was later promoted to Expert
• Specialized in analyzing official statistics and handling complex datasets to extract meaningful insights
• Successfully managed and coordinated over 20 ongoing projects annually, collaborating with cross-functional teams to drive data-driven decision-making and process optimization
• Conducted seasonal adjustment analysis using JDemetra+ for over 1,000 time series annually, including GDP, foreign trade and consumer confidence indices
• Applied forecasting, backcasting and nowcasting techniques for time series, analyzing complex datasets and high-frequency time series
• Conducted econometric modeling to assess economic trends and policy impacts, applying statistical techniques to improve forecasting accuracy
• Built statistical models, including ARIMA models, determining key variables using both statistical tests and economic significance
• Ensured data integrity by detecting anomalies, cleaning datasets, performing outlier detection and improving data quality across databases
• Automated data preprocessing and transformation workflows using Python and SQL, reducing manual effort and improving efficiency
• Developed dashboards and reports in Excel and R Markdown to visualize and present results effectively
• Assisted other departments with data analysis needs and provided training on data analysis, time series and seasonal adjustment
• Prepared methodology reports for official statistics and communicated findings and insights to both technical and non-technical stakeholders
• Collaborated with international partners (EUROSTAT, ICON Institute) to harmonize methodologies
• Worked on statistics including foreign trade indices, gross domestic product, labour force statistics, foreign trade statistics, turnover indices, industrial production index, consumer price index, consumer confidence, labour input, labour cost and earnings statistics, retail sales indices, services, retail trade and construction confidence

• Performance optimization and centralization of reporting by creating data models using SSMS (SQL) & SSAS (DAX) and integrating data via SSIS
• Optimizing and extending the current PowerBI dataset (in parallel until the SSAS data model is ready)
• Expanding current reports (migrating reporting to SSAS source after building the SSAS data model)
• Conducting regression analyses, cohort analyses, price/quantity analyses, and strategy project success analyses
• Training internal team members