Data Science Experts in Cologne
for reliable models and decisions, matched in minutes with vetted and available freelancersHire experts who turn complex data into forecasts, experiments and production-ready machine learning workflows across Python, SQL, cloud platforms and modern analytics stacks. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Cologne, who have recently used Data Science
Michael K.
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
- Management of the architect pool
- Support for program management in setting up the transformation project based on agile methods
- Consideration of regulatory requirements for IT projects in the federal administration
Jonas H.
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 R.
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 W.
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
Halil O.
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.
Emmanouil T.
Last position:
Senior Analytics Engineer at Trade Republic Bank GmbH
- Implementation of analytics and automation solutions for the Anti Financial Crime business unit
- Providing the infrastructure, including reusable data models and feature ingestion for production ML and rule based models in the areas of Account Take-Over and Card fraud detection, as well as Customer Risk Assessment
- Tools used: Snowflake, dbt, Looker, AWS, Python, Airflow, Metaflow
Rodion O.
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.
Christian H.
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 B.
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 D.
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 F.
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 K.
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 P.
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 N.
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 J.
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 (Germany: 14 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: 97%)
Master's degree or higher
69% (Germany: 80%)
Doctorate
15% (Germany: 22%)
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, Greek
Speak two or more languages
100% (Germany: 97%)
Based on our profile pool as of 19 Sep 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Science experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (73%)
- Education (47%)
- Banking and Finance (47%)
- Insurance (47%)
- Healthcare (40%)
- Professional Services (40%)
- Retail (33%)
- Telecommunication (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Science delivers
Data Science combines statistics, programming, domain knowledge and machine learning to turn raw information into useful decisions. Professionals build forecasting systems, recommendation engines, customer models, anomaly detection and analytical products. The work often spans data preparation, experimentation, model development and communication of results.
Core methods and outputs
A strong data science project connects a clear business question with measurable evidence and a maintainable result. Typical deliverables include:
- Exploratory analysis that reveals patterns, gaps and risks
- Predictive models for demand, churn, fraud or quality
- Experiments that test product or process changes
- Dashboards, reports and decision-ready explanations
Ecosystem and tooling
Python and SQL are central, with libraries such as pandas, NumPy, scikit-learn, PyTorch and TensorFlow used for analysis and modelling. Specialists may also work with Jupyter, Spark, dbt, Airflow, Docker and cloud services for storage, processing and deployment. Good practice includes version control, reproducible environments, feature engineering and model monitoring.
When companies need specialists
Companies bring in freelance expertise when internal teams need a focused capability, an independent view or faster progress from prototype to production. This is common during a new analytics initiative, a migration to a modern data stack or the introduction of machine learning into an established product. In Cologne, professionals may support local teams on site, remotely or in a blended setup, depending on access and collaboration needs.
Signs of strong expertise
Quality is visible in the connection between technical choices and business outcomes. Look for professionals who can explain assumptions, validate data quality and compare a complex model with a simpler baseline. They should also understand privacy, bias, interpretability, deployment constraints and the operational cost of keeping models useful.
Collaboration and delivery
The best engagement starts with a defined decision, accessible data and an agreed path to adoption. Freelancers should clarify ownership, success criteria, review points and handover needs before building. They can collaborate with product, engineering and analytics teams in English or German, while documenting datasets, features, experiments and operating procedures for long-term use.
Frequently asked questions
Before you brief your next project: the most common questions about Data Science.
Data Science is used to extract insight from structured and unstructured data and support better decisions. Common applications include demand forecasting, fraud detection, recommendations, pricing analysis, quality monitoring and customer segmentation.
Data Science often adds statistical modelling, machine learning and experimentation to descriptive analysis. Business intelligence usually focuses on reporting what happened, while data analytics can cover both descriptive and diagnostic work; the boundaries overlap in practice.
A capable Data Science specialist often combines Python, SQL, statistics, data visualisation and machine learning with domain knowledge. Experience with cloud storage, data pipelines, MLOps, APIs and stakeholder communication is valuable when a model must run in a real product.
The right level depends on the work rather than a fixed number of years. A focused analysis may need strong statistical and communication skills, while production machine learning requires experience with data quality, deployment, monitoring and model maintenance.
Data Science projects are often suitable for remote collaboration because analysis, notebooks and model reviews can be shared digitally. On-site work in Cologne can still help when specialists need close contact with operational teams, sensitive data environments or business stakeholders.
Before engaging Data Science expertise, define the decision the work should improve, the available data, access constraints and how success will be assessed. It also helps to clarify whether the expected result is an analysis, a validated model, a production service or a handover to an internal team.
A strong Data Science freelancer explains data limitations, establishes a credible baseline and validates results against the real business context. Ask how they handle leakage, bias, missing data, reproducibility and monitoring rather than judging quality from model complexity alone.
Data Science work may include problem framing, data profiling, feature preparation, modelling, evaluation and a clear presentation of findings. If the result must operate continuously, the engagement may also cover deployment, documentation, monitoring and knowledge transfer.
The average hourly rate of freelancers in Cologne, Germany who have used Data Science in their recent projects is 99 €, which corresponds to a daily rate of about 789 € 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, 69% hold at least a Master's degree, and 15% 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 Greek (7%).
The most common industries among freelancers in Cologne, Germany who have used Data Science in their recent projects are Information Technology (73%), Education (47%), and Banking and Finance (47%).
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 (60%).
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
