Data Science Experts in Cologne
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Meet FRATCH Experts in Cologne, who have recently used Data Science
Halil Oeztoprak
Last position:
Senior Cloud Operations & DevSecOps Engineer (Azure / Terraform / CI-CD) at KfW Bankengruppe
Regulated environment within a German banking group (approx. 8,500 employees, hybrid cloud strategy).
Responsible for operating, provisioning, and continuously securing business-critical platforms – including a GenAI chat application, a big data/AI platform, and data science workspaces based on Azure Virtual Desktops and VMs. Ownership of Azure DevOps projects for ShaiHulud and React2Shell, as well as BSI alerts – Security Operations improvements across the SDLC.
Deployment responsibility for the GenAI chat application, big data/AI platform (BDAI), and data science workspaces (AVD/VM-based) in the respective landing zones.
Deployment & release management: end-to-end responsibility for deploying portal and service applications across multiple Azure landing zones, including technical approvals, compliance with development team deployment guidelines, and ensuring ITIL-based change and release processes via ServiceNow.
Azure landing zones & network architecture: design, provisioning, and operation of Azure landing zones for 3-tier web applications with enhanced network segmentation, VNet peering, hub-and-spoke architectures, private endpoints, and firewall integration across separate subscriptions and tenants.
Azure DevOps governance & operations: ownership of the Azure DevOps organization, including projects, repositories, and CI/CD pipelines; implementation of governance requirements such as branch policies, approval gates, permission models, and audit-ready operating structures.
Infrastructure as Code (Terraform): design, implementation, and operation of a modular Terraform architecture for standardized cloud infrastructure deployment, including state management, provider versioning, reusability, and policy-as-code approaches.
CI/CD pipeline engineering: design, operation, and optimization of complex YAML-based CI/CD pipelines with multi-stage deployments, template standardization, self-hosted agents, integrated secret management, and automated quality and security checks.
Git migration & platform consolidation: planning and execution of repository and pipeline migration from Azure DevOps to GitLab CI/CD, including automated scripts, full Git history transfer, pipeline porting, and platform consolidation.
Container & platform operations (AKS): operation and security assessment of containerized workloads on Azure Kubernetes Service, centralization of on-premises container registries for ACR.
OpenShift (OCP) security reviews: security assessment of code baselines, build pipelines, and deployment processes for on-premises OpenShift clusters with critical applications, and derivation of specific hardening recommendations.
Shift-left security & DevSecOps transformation: introduction of a company-wide shift-left approach for early security integration in development and deployment processes, enabling developers to perform self-led security checks and sustainably reduce vulnerabilities before production (IDE integrations, pre-commit hooks, local scanners).
Software supply chain security: analysis and mitigation of supply chain risks in NPM- and Yarn-based applications through dependency audits, CI/CD pipeline hardening, token rotation, and restriction of risky build and lifecycle mechanisms.
Frontend & framework security (React / Next.js): security assessment and coordination of critical vulnerability remediation across platform applications and web frameworks, including coordination and complementary technical mitigations with all teams following BSI alerts.
Software composition analysis (SCA): introduction and operation of automated vulnerability scans for container images, pipelines/artifacts, and third-party dependencies, including SBOM exports within CI/CD pipelines.
SAST/DAST integration: design and piloting of static and dynamic application security tests in close collaboration with security architecture and development teams, for continuous improvement of code and runtime security, and establishing operational acceptance tests.
Artifact & registry consolidation: analysis and consolidation of all package and container repositories for service applications and AKS workloads, aiming for a centralized, secured registry strategy with centralized vulnerability scanning and governance.
Dependency-Track & SBOM strategy: advising the compliance board on introducing a central SBOM and vulnerability management platform to increase enterprise-wide dependency transparency and accelerate CVE response capability.
CI/CD pipeline hardening: security analysis and cleanup of the existing pipeline landscape by removing unused pipelines, improving secrets hygiene, implementing least-privilege principles, and isolating build agent environments.
Azure Web Application Firewall (WAF) optimization: analysis and tuning of existing Azure WAF rules (OWASP Top 10 Core Rule Set, DSR/SDC, custom rules) to defend against known vulnerabilities and exploit patterns, including reducing false positives and improving threat detection.
Documentation & stakeholder communication: creating and maintaining technical documentation, runbooks, and architecture overviews in Jira and Confluence, as well as active knowledge transfer between operations, development, security, and compliance stakeholders.
Michael Kunz
Last position:
Enterprise Architect, Lead Architect of the transformation program and coach at Swiss Ministry
- Development of the overall architecture
- Support for the respective workstreams in developing architectures in the areas of infrastructure, data centers, security, and network topology
- Coordination of the architect pool
- Support for program management in building the transformation project based on agile methods
- Consideration of regulatory requirements for IT projects in the federal administration
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.
Jonas Haid
Last position:
Senior Performance Marketing Manager at HDI Versicherung AG
- Developed data-driven performance strategies and managed cross-functional agency teams.
- Led KPI forecasting, budgeting, and implemented scalable creative solutions.
- Linked creative insights with analytics to increase marketing efficiency.
- Developed inspiring campaigns based on brand strategy and data-driven insights.
- Performed budget planning, forecasting, and full KPI accountability.
- Led and executed an agency pitch for performance marketing.
Fahad Razzaq
Last position:
Data Science – Operations Optimization at Netto-marken
Project: Digitalization of Warehouse Processes | Building a Data Analytics Platform.
- Built a web-based workforce allocation system that digitized daily shift planning by matching worker expertise to operational zones, replacing manual coordination with a structured workflow adopted across the site, saving supervisors time on daily planning.
- Developed a real-time operational visibility dashboard giving supervisors a live view of task throughput and outstanding workload across warehouse zones throughout the day, helping reduce overtime and idle labour costs.
- Developed a slotting optimization solution to improve warehouse picking efficiency and reduce picking time per order, working directly with operations teams from concept through production deployment.
Technologies used: Python, Django, PostgreSQL, Pandas, NumPy, HTML, Java, JavaScript, Docker, Kubernetes, AWS, Power BI, GitHub Actions CI/CD, GitOps, Claude, OpenAI
Sophia Wagner
Last position:
AI Engineer & Technical Consultant at Freelance
- Delivered ML pipelines for OCR, semantic search, and computer vision
- Integrated Azure AI Agents and GPT workflows for automation and QA
- Deployed cloud-based FastAPI services with scalable architecture
- Created integration docs and advised on LLM production readiness
Christian Hunkirchen
Last position:
Developer at Opereon Consulting GmbH
- Developed a shop website
- Integrated an AI language model
- Developed tools for AI-powered webhooks
- Technical tools: REACT.js; Elevenlabs; MCP; n8n; HTTP
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
André Filip
Last position:
GenAI Product Owner at OW Media Solutions GmbH
- Designed and led the development of an automated short-video generation system.
- Built a scalable AWS backend using Step Functions, Lambda, S3, ECS Fargate, and DynamoDB.
- Developed video rendering with OpenCV and FFMPEG; ensured maintainable Python code.
- Supervised and mentored a Python developer and trained the client in AI workflows.
- Decreased end-to-end production time from hours to minutes.
- Created a modular, extensible architecture designed to support future AI models.
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
Pappu Prasad
Last position:
Senior Cloud Consultant (AWS Services and Consulting) at devoteam GmbH
- Developed automated ETL pipelines with AWS Glue and Athena to ensure consistent data quality and governance requirements
- Implemented validation, anonymization, and encryption measures for data in compliance with GDPR
- Optimized cloud costs by introducing FinOps practices and increased transparency for business units
- Monitored performance, performed root cause analyses, and ensured adherence to SLAs
- Supported data and solution architects in building scalable data models for ML and analytics scenarios
Marian Neunkirchen
Last position:
Senior PMO at Commerzbank AG
- The project's goal was to set up a ticketing system (ServiceNow).
- Implementing and carrying out standard PMO and Scrum Master processes such as risk and issue/impediment management
- Coordinating and tracking provided services
- Monitoring project progress and project reporting, as well as maintaining project planning in an agile environment
- Creating JIRA dashboards to track sprints
- Tracking sprints for completion status, highlighting risks and impediments
- Conducting management retros, developing and following up on action points
- Technologies: MS Excel, MS PowerPoint, Microsoft 365, JIRA, Confluence
- Project languages: English, German
Valon Jashari
Last position:
Cybersecurity and Data Scientist Engineer at Freelancer
- Cyber Security (IT, OT, Ethical Hacking & Pen Testing)
- Data Science (Machine Learning, Deep Learning, Data Engineer and Data Analytics)
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
15 years
Position duration
1.6 years (Germany: 2.2 years)
Positions per freelancer
11 (Germany: 9)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Education, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Operations
Bachelor's degree or higher
92% (Germany: 96%)
Master's degree or higher
67% (Germany: 78%)
Doctorate
17% (Germany: 22%)
Certifications per freelancer
5 (Germany: 3)
Most common languages
German, English, Spanish
Speak two or more languages
100% (Germany: 96%)
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 Data Science
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 that matters
Data science turns raw data into answers the business can use. It blends analysis, statistics, modeling, and domain knowledge to support forecasting, segmentation, detection, and experimentation. Strong specialists keep the focus on a clear question, not just on building models.
Typical deliverables
- Exploratory analysis and feature work
- Predictive models and validation reports
- Dashboards and decision-ready summaries
- Data pipelines for repeatable analysis
- Experiment design and result interpretation
Tooling and stack
The stack often includes Python, R, SQL, Jupyter, pandas, scikit-learn, and notebook-based workflows. Depending on the setup, specialists also work with cloud data warehouses, version control, orchestration tools, and BI tools. The right choice depends on the data, the team, and the production path.
When companies bring in help
Businesses hire freelance specialists when a project needs fresh capacity, a difficult model, or help turning messy data into something usable. That is common for product analytics, forecasting, customer behavior analysis, and internal reporting. In Cologne, this often fits teams that want flexible support across commercial, industrial, logistics, and media-driven work.
What good specialists do
A strong specialist asks the right questions before modeling. They clean data carefully, document assumptions, and explain trade-offs in plain language. They also know when a simpler analysis is better than a complex model.
Working setup
- Clarify the business question and success criteria
- Review data quality, access, and privacy needs
- Agree on remote or on-site collaboration early
- Define handover format for notebooks, code, and findings
- Keep stakeholders aligned on interpretation and next steps
Frequently asked questions
Before you brief your next project: the most common questions about Data Science.
A strong Data Science expert turns data into analysis, forecasts, or models that support a decision. That can include cleaning data, testing hypotheses, building predictive models, and explaining the result in a way the team can use. The best specialists also make their work repeatable, so the output is easier to maintain later.
Choose Data Science when the question needs prediction, pattern detection, or statistical modeling, not just reporting. BI is better for stable dashboards and regular business views, while data science goes deeper into uncertainty and behavior. Many projects use both, but they solve different problems.
A good Data Science freelancer usually brings SQL, Python or R, statistics, data cleaning, and model evaluation. Many also work with notebooks, cloud data tools, and visualization software. If the project is product-facing, domain knowledge and clear communication matter just as much as the technical stack.
You do not need a fully defined model before bringing in Data Science help, but you do need a real business question. The best results come when the team can describe the data sources, the decision to support, and the constraints around privacy or access. A specialist can help shape the method once those basics are clear.
Often, yes. Many Data Science tasks can be done remotely if the data access, security rules, and feedback loops are in place. On-site work can help at the start of a sensitive project or when close collaboration with business teams is important, including for companies in Cologne and nearby.
Data Science is broader and often starts with understanding the problem, the data, and the business impact. Machine learning engineering focuses more on production systems, deployment, and operational reliability. In practice, one specialist may cover both areas, but the project goal should decide which emphasis you need.
Look for clear problem framing, careful data handling, and explanations that make sense without jargon. A strong Data Science specialist can show prior work, describe trade-offs, and explain why a simpler approach may beat a complex model. Quality also shows up in how well the work can be reviewed, reused, and handed over.
Yes, but the scope must be realistic. Data Science projects often start with incomplete tables, inconsistent definitions, or missing history, so a good specialist will spend time on cleaning and validation before modeling. If the data problems are severe, the first deliverable may be a data audit rather than a model.
The average hourly rate of freelancers in Cologne, Germany who have used Data Science in their recent projects is 101 €, which corresponds to a daily rate of about 805 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used Data Science in their recent projects, 92% hold at least a Bachelor's degree, 67% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Cologne, Germany who have used Data Science in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 1.6 years.
The most common languages among freelancers in Cologne, Germany who have used Data Science in their recent projects are German (100%), English (93%), and Spanish (7%).
The most common industries among freelancers in Cologne, Germany who have used Data Science in their recent projects are Information Technology (79%), Education (43%), and Banking and Finance (43%).
The most common business areas among freelancers in Cologne, Germany who have used Data Science in their recent projects are Information Technology (100%), Business Intelligence (93%), and Product Development (64%).
Main locations of FRATCH Experts, who have recently used Data Science
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 
Stuttgart 
Dusseldorf 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
