R Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used R
Dmitry Pankov
Last position:
Freelance Digital Marketing Analyst at Freelance
- Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
- Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
- Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
- Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.
Umut GĂĽlac
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Michael Nelz
Last position:
Senior ML Engineer, AI Engineer at Lanxess AG
- Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
- Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
- Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.
Daryoosh Dehestani
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
Hervé Teguim
Last position:
Senior Data Engineer at Schweizerische Post AG
Tools: Fabric, AWS, dbt, Power BI, SQL, DWH, R, Python
- Supported customers in implementing an architecture design for extracting and preparing data
- Planned the design and implementation of the BI and DWH platform
- Ensured the scalability and performance of the data platform
Kiriakos Krastillis
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
maturing their API Practices on both, a Business and Technology level. My role encompasses strategy, architecture, developer advocacy as well as hands on software engineering, enabling both technical teams and business leadership to adopt and act on API- centric principles effectively. Coincidentally, we also establish GitOps, DX and Platform Best practices with this project.
Highlights:
- Aligning executives with the initiative by clarifying strategy, replacing misconceptions and myths with facts, clarifying the value of existing assets and enabling informed decision-making
- Formulating a way forward for API Lifecycle Management at OTTO
- Driving platform progress and fostering developer engagement by hands-on engineering work towards strategic goals
API Lifecycle Management, Team Topologies, Organizational Evolution, Regulatory, Platform Advocate, Developer Platform, Communities of Practice, Terraform, Kotlin, Kafka, Kong, WSO2, Apigee, Gravitee, Backstage, AsyncAPI, OpenAPI, API Design, AWS, react, nodejs, typescript, redocly, reactive programming, CDC, golang, gingonic, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Philipp Grunert
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- 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
Justina Kmiecik
Last position:
Freelance Consultant for Change & Data Transformation at Freelance Fast Data Consulting
Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present
- Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
- Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.
Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025
- Concept development and solution design for new end-to-end processes including technical interfaces
- Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
- Analysis and validation of data models
- Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
- Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
- Documentation and comments on technical and business requirements to support implementation in agile squads
Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present
- Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
- Development of business solution concepts for migration to the target system, including system integration and data flows
- Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
- Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
- Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.
Bastian Vasterling
Last position:
Managing Director / Partner at SMATRA Trading Group & Consultancy
- Establishing and leading the SMATRA Trading Group & Consultancy with a focus on market entry and development projects between Europe and Asia-Pacific.
- Consulting and trading in premium consumer goods (coffee & tea), including building supply chains, brand partnerships, and sales channels (e.g. Hong Kong).
- Developing an expert network for market analysis, market entry, digital transformation, and sustainable business models.
- Supporting and coaching founders and medium-sized companies in building scalable, self-managed teams beyond traditional hierarchy structures.
Nitin Bhardwaj
Last position:
Financial Analytics Lead at Independent Consultant
Led FP&A tech transformation for a 9-figure business – from resolving legacy technical debt to leading AI-native EPM implementation
- Driving end-to-end FP&A transformation, from architecture redesign through EPM tool selection to rollout
- Ran evaluation of 12+ EPM platforms, from vendor negotiation to selection framework tied to long-term planning
- Diagnosed constraints in financial planning architecture, presented findings to the CFO, and secured executive mandate to redesign FP&A infrastructure from the ground up
Sarvesh Lunia
Last position:
Data Analytics for Renewable Energy Integration at Harz University
- Created data pipelines and visualization tools to support sustainable energy decision-making
- Developed insights that could optimize renewable energy deployment and grid integration strategies
Volker Haase
Last position:
Data Analyst at Optaro GmbH
Creation of workflows for generating the data basis for the article import of a web shop: combining data from several sources, analyzing the requirements, designing the process with Jupyter Notebooks and Knime. Also creating code for automation in Python using Polars and Pandas.
Processing the source data, filtering and merging the source files and creating the needed intermediate products, creating the upload files, plausibility checks, quality checks.
Technologies used: PyCharm, Python, Jupyter Notebooks, SQL, Knime. Pandas, Polars
Ashwin Parthasarathy
Last position:
Freelance Data Scientist at Mercor Intelligence
- Architected and deployed end-to-end machine learning pipelines across classification and prediction datasets, ensuring robustness and reproducibility through MLOps best practices.
- Contributed directly to LLM model output accuracy improvement by designing and engineering specialised prompts grounded in end-to-end ML and SciML pipeline logic.
- Developed training data for large language models by formulating coding problems that models could not resolve and subsequently documenting the correct solutions.
Rodion Orlinskiy
Last position:
Founder, CTO & Managing Director at MYNR Product Mining GmbH
- Responsible for the architecture and development of an AI-native SaaS platform for industrial product portfolio management.
- Designed the modern data platform architecture on Azure for scalable analytics and enterprise data integration.
- Built enterprise data ingestion and transformation pipelines across complex industrial system landscapes.
- Developed graph-based representations of product structures and dependencies for analytical reasoning.
- Designed and implemented an agentic AI framework for AI-supported decision workflows.
- Built scalable analytical microservices and integrated reporting through modern BI technologies.
- Coordinated backend, AI, and frontend development across the MYNR platform stack.
André Howe
Last position:
Linux IT Admin at ReiserST
- 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.
Discover over 15,000 top freelancers
Statistics of experts using R
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
2.8 years
Positions per freelancer
9
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Education, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
99%
Master's degree or higher
81%
Doctorate
27%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
99%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Germany using R
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What R is
R is a language and environment for statistical computing, data analysis, and visual reporting. Teams use it to explore datasets, test hypotheses, and turn raw information into models, charts, and decision-ready outputs. It is common in analytics-heavy work where reproducible results matter.
What it does
- Data cleaning, shaping, and validation
- Statistical analysis and forecasting
- Visualisation with ggplot2 and related tools
- Reporting with R Markdown and Quarto
- Package-based workflows for repeatable analysis
R is often chosen when the work is more analytical than transactional. It fits projects that need transparent methods, clear documentation, and outputs that others can review and rerun.
Ecosystem and tools
A strong R specialist works comfortably with tidyverse, dplyr, tidyr, ggplot2, data.table, Shiny, and Quarto. They also know how to connect R to databases, APIs, spreadsheets, and file-based data sources. In many projects, the real value is not just code, but the structure around it.
Good work in R also means version control, tested scripts, and clean project setup. That makes handover easier when a team needs to maintain analysis after the freelancer leaves.
When companies bring in help
Companies usually look for freelance R expertise when internal teams need extra analytical capacity or a project has a short delivery window. It is also useful when a reporting setup needs refactoring, a model needs validation, or a Shiny app needs targeted changes.
- Dashboards and interactive apps
- Research and market analysis
- Data science prototypes and model reviews
- Automated recurring reports
- Legacy R code cleanup
What strong professionals deliver
Strong R professionals write clear, reusable code and explain assumptions in plain language. They know how to choose the right package for the task, and they can defend their approach when the analysis affects business decisions. They also avoid fragile scripts and hidden manual steps.
For companies in Germany, that often means support for mixed teams where English code and German business context meet. Remote collaboration is common, but on-site work can help when data access or stakeholder workshops are sensitive.
How to judge fit
Look for specialists who ask about the data source, the audience, and the final delivery format before they start. Good R work is specific: an analysis notebook, a reproducible report, an app, or a model pipeline with clear outputs. If the brief is vague, the best experts will push for scope first.
Ask for examples of similar work in analytics, research, reporting, or Shiny. The strongest freelancers can explain why they chose a package, how they checked results, and what a non-technical reviewer will actually receive.
Frequently asked questions
Key details about R, drawn from the questions we get asked most.
A strong R specialist usually works on statistical analysis, data preparation, forecasting, and reporting. It is also common for reproducible research, dashboards, and Shiny apps that present data in a usable way. Companies choose it when the task depends on careful analysis and clear documentation.
R is often preferred for statistics, research-style analysis, and polished visual reporting. Python is broader for general software tasks, but R remains very strong when the focus is on data exploration, modeling, and communication of results. The better choice depends on the team’s existing stack and the kind of deliverable.
A good R freelancer usually knows tidyverse, ggplot2, data.table, and Quarto or R Markdown. Database access, SQL, Git, and basic understanding of statistics are also valuable. For app work, Shiny experience matters a lot.
For simple reporting or data cleaning, a focused R specialist may be enough. For modeling, package integration, or legacy code refactoring, you want someone who has handled similar complexity before. The more business-critical the output, the more important proven delivery becomes.
Choose R professionals with Shiny experience when you need an interactive app, internal dashboard, or data entry tool. They should understand reactive logic, UI structure, and how to keep the app maintainable. If the app must connect to live data, database and deployment knowledge are important too.
Yes, R work is often a good fit for remote collaboration, especially for analysis, reporting, and code review. In Germany, many projects still combine remote delivery with short on-site sessions for stakeholder alignment or access to internal data. Clear documentation helps the handover either way.
A strong R specialist writes reproducible code, explains assumptions clearly, and delivers outputs that others can maintain. Look for clean project structure, sensible package choices, and examples of work similar to your use case. Good communication matters as much as technical depth.
For many analytics and research projects, R is still an excellent choice. It is especially strong when statistical methods, visualisation, and transparent reporting are central. If the project is mainly product software, another language may fit better, but for analysis-heavy work R remains highly practical.
The average hourly rate of freelancers in Germany who have used R in their recent projects is 93 €, which corresponds to a daily rate of about 744 € based on an 8-hour working day.
Of the freelancers in Germany who have used R in their recent projects, 99% hold at least a Bachelor's degree, 81% hold at least a Master's degree, and 27% hold a doctorate.
On average, freelancers in Germany who have used R in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers in Germany who have used R in their recent projects are German (100%), English (99%), and French (28%).
The most common industries among freelancers in Germany who have used R in their recent projects are Information Technology (66%), Education (45%), and Professional Services (43%).
The most common business areas among freelancers in Germany who have used R in their recent projects are Information Technology (76%), Business Intelligence (73%), and Product Development (66%).
Main locations of FRATCH Experts, who have recently used R
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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