R Experts in Cologne
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Meet FRATCH Experts in Cologne, who have recently used R
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.
Kevin Baßler
Last position:
Procurator and AI Lead at ValueData GmbH
- Serve as AI lead for life-science solutions, integrating advanced AI models directly into company workflows and ensuring seamless deployment.
- Design and implement deep learning architectures (PyTorch, Keras) for complex biomedical challenges, including cell segmentation, multimodal omics analysis, and prediction of point clouds.
- Develop and deploy robust LLM-based systems, including RAG architectures and agentic workflows using LangGraph, to facilitate natural-language interaction with complex medical data.
- Lead cross-functional initiatives to apply foundation models and explainable AI (xAI) to clinical and evolutionary algorithms.
Dmitriy Drichel
Last position:
Freelance Senior Data Scientist at Merck KgaA
- AWS
- Genedata Profiler
- Data Lake
- APIs
- Rstudio
- GitLab
- Python
- R
- Data acquisition, integration, and simulation
- Multiplex immunofluorescence
- Copy-number variation calling
- HLA typing and loss-of-heterozygosity analysis
- RNA expression analysis
Aman Maharjan
Last position:
Guest Researcher at Max Planck Institute for Neurobiology of Behavior
- Coordinated feedback and milestones with international co-authors to streamline publication
- Directed data curation and final analysis using Python and Matlab
- Accelerated the final publication timeline by efficiently managing figure preparation and data traceability
Jeanne Yap
Last position:
Process Engineering Intern at Procter & Gamble
- Independently initiated and deployed automated validation workflows using Python, cutting manual processing by 58% and improving efficiency
- Developed a machine learning model for synthetic defect generation, reducing downtime and production costs; deployed locally and via Databricks and Azure AI Factory
- Utilized a small dataset of image data from the production lines and extended this dataset with training on models like cycleGAN and pix2pix
- Built and optimized the Linux-based development environment for training 3D models; maintained reproducibility via GitHub
- Presented technical insights to cross-functional teams (engineers, QA, project managers), ensuring alignment of ML solutions with operational needs
Denis Kirpicev
Last position:
Management Consultant at Freelance Management Consultant
Implementation of custom reporting solutions for financial KPIs aligned with specific business requirements
Development of a machine learning application that achieved a 250% performance improvement
Data Architect "Production-Oriented Quality Assurance" (03/2024–09/2024):
Design and implementation of an analytics platform to detect quality deviations in manufacturing
Build of a scalable data lakehouse architecture on Databricks in combination with SAP ERP data via SAP Datasphere
Close collaboration with the SAP team to harmonize bill of materials and order data
Visualization of KPIs to support shopfloor management
Lead Data Engineer "Sales Performance Monitoring" (08/2023–12/2023):
Design and implementation of a Databricks-based platform for analyzing sales figures and promotion effects
Integration of SAP SD data via SAP BW/4HANA
Use of Azure DevOps to orchestrate ETL jobs and deploy workflows
Technical Project Lead "Cloud Migration & Data Strategy" (02/2023–05/2023):
Migration of a heterogeneous data warehouse stack to a modern cloud architecture on Azure with Databricks as the central processing platform
Development of a governance-compliant data architecture to integrate SAP financial data and non-SAP sources
Technologies: Databricks, Delta Lake, Python, SAP Datasphere, Azure DevOps, PowerBI, SQL
Filipp Trigub
Last position:
Multi-chain LLM copilot for academic teaching and studying at Infolab.ai
- Build a sophisticated AI copilot to augment the students’ learning experience and provide AI-derived insights to professors.
- Build a multi-chain LLM system adapting to user needs at its own accord with a Weaviate vector DB based RAG system and evaluated it with Ragas.
- Build responsive react frontend, and backend systems handling auth, data management and auxiliary services as a RESTful API.
- Deployed and managed the app to the cloud in a production environment including the CICD via multi-stage deployment.
Nico Schäfer
Last position:
Quantitative modeling and model development, statistical data analysis, reporting at DB InfraGO / Brockmann & Büchner Partnergesellschaft
- Technical project management, requirements management, and design to guide the data team in developing a predictive maintenance model for DB InfraGO's maintenance planning.
- Statistical modeling and analysis programming with R Studio for fault analysis in preventive maintenance: multivariate modeling using quasi-Poisson, negative binomial, lasso, offset, splines, RandomForest.
- Implementation of various R Shiny dashboards.
- Sparring partner and requirements management for data engineering, data modeling, and ETL pipeline in Tableau Prep.
Nhu Loc Thuy Tran
Last position:
Ph.D. Researcher in Quantitative Genetics & Computational Biology at University of Cologne (CEPLAS – Cluster of Excellence in Plant Sciences)
- Generated and analysed large-scale RNA-seq data (>800 samples) using R, Python, and high-performance computing (HPC/Linux) systems.
- Integrated multi-omics data (genomic, transcriptomic, and phenotypic); applied Bayesian approaches and machine learning to study gene expression variation and inheritance of complex traits.
- Mentored B.Sc. and M.Sc. students in experimental design, programming in R/Python/Bash, biostatistics, data visualisation and scientific presentations.
Sylvia Berge
Last position:
Freelance Digital Communications Consultant, Social Media Marketing Expert & Project Lead
- Strategy | Concept | Consulting | Project Management | Editing | Copywriting | Reporting | Format Development | Channel Optimization
References · mobile.de | mo:re Conference | mobile.de/more · mediakompetent (journalist, JTI) · Federal Employment Agency · Williams Racing (Formula 1) · Catholic Media Congress 2022
- I look forward to a message or email at [email]
Markus Schnabel
Last position:
Freelance Photographer and Videographer at Medianautiker
Discover over 15,000 top freelancers
Statistics of experts using R
Aggregated from the professional profiles of matched freelancers.
Experience
14 years
Position duration
2.3 years (Germany: 2.8 years)
Positions per freelancer
7 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Research and Development
Top industries
Education, Information Technology, Biotechnology
Certification focus areas
Information Technology, Business Intelligence, Logistics
Bachelor's degree or higher
100% (Germany: 99%)
Master's degree or higher
100% (Germany: 81%)
Doctorate
40% (Germany: 27%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 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 Cologne 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 Cologne 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
Data work
R is built for data analysis, statistics, and clear reporting. Companies use it to clean datasets, explore trends, validate assumptions, and turn raw numbers into decision support. It fits projects where reproducible results matter.
Common delivery
- Statistical analysis and forecasting
- Dashboards with Shiny
- Data preparation and validation
- Reporting with R Markdown or Quarto
- Package development for internal use
Ecosystem
Strong R specialists work fluently with the tidyverse, ggplot2, dplyr, data.table, and CRAN packages. They also understand how to connect R with SQL, APIs, and cloud data sources. Good code is readable, reproducible, and easy to maintain.
When to bring help
Freelance R expertise is useful when a team needs extra hands for an urgent analysis, a one-off research project, or a reporting layer that must be reliable. It also helps when existing scripts are slow, messy, or hard to hand over. In Cologne, this is common in analytics-heavy teams, agencies, and research settings.
What strong specialists do
A strong R professional writes clean functions, tests critical logic, and avoids fragile notebooks for core work. They can explain the method behind the result, not just the output. They also know when to keep work in base R and when to use a package or a more modern workflow.
Working model
R projects can run fully remote, but some teams prefer on-site workshops for data access, stakeholder review, or model validation. The best setup is the one that keeps communication tight and the data secure. For Cologne-based teams, hybrid work is often a practical middle ground.
Frequently asked questions
Everything clients usually want to know about R, in one place.
Companies usually hire R specialists for statistical analysis, reporting, data cleaning, and Shiny apps. They are also brought in for reproducible research, package work, and workflows that need clear documentation. R fits projects where the result must be easy to audit and repeat.
R is often the better choice when the work is heavily statistical, exploratory, or report-driven. Python is broader for general software tasks, while R is especially strong in analysis, visualization, and academic or regulated reporting contexts. Many teams use both, but keep R for the parts where it is strongest.
A strong R freelancer usually knows tidyverse, ggplot2, data.table, SQL, and at least one reporting tool such as R Markdown or Quarto. Shiny is important when the project needs interactive apps. Experience with Git and clear data handling is also a plus.
It depends on the scope, but R work is rarely just about writing code. A useful specialist should be able to explain data choices, handle missing values, and write reproducible analysis. For larger projects, look for someone who has already delivered similar reporting, modeling, or dashboard work end to end.
Yes, most R work can be done remotely if the data access and review process are set up well. On-site time helps when stakeholders want workshop-style analysis, sensitive data discussion, or close alignment on metrics. Many Cologne teams choose a hybrid setup for that reason.
Look for clean scripts, clear function structure, and results that can be reproduced from raw data. A good R specialist should explain why they chose a method, not just show charts. Check whether they document assumptions, edge cases, and handover steps clearly.
R is the language, and GNU R is the common open-source implementation people usually mean when they say R. In practice, searchers may use either term, but the work is the same: analysis, statistics, graphics, and reporting. The ecosystem around it is centered on CRAN packages and related tools.
Yes, R specialists who build Shiny apps need more focus on interaction, state, and user flow, while package work needs careful API design, testing, and documentation. Both require solid coding habits, but the delivery standards are different. Ask for examples that match your exact project type.
The average hourly rate of freelancers in Cologne, Germany who have used R in their recent projects is 86 €, which corresponds to a daily rate of about 684 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used R in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 40% hold a doctorate.
On average, freelancers in Cologne, Germany who have used R in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Cologne, Germany who have used R in their recent projects are German (100%), English (100%), and French (27%).
The most common industries among freelancers in Cologne, Germany who have used R in their recent projects are Education (64%), Information Technology (55%), and Biotechnology (45%).
The most common business areas among freelancers in Cologne, Germany who have used R in their recent projects are Business Intelligence (73%), Information Technology (64%), and Research and Development (64%).
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.
Berlin 
Hamburg 
Munich 
Frankfurt 
Dusseldorf 
Essen Request a free demo
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Philipp Thomaschewski
FRATCH CEO
