Data Mining Expert in Germany
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Meet FRATCH Experts in Germany, who have recently used Data Mining
Enver B.
Last position:
Interim Manager Data Protection Projects at Telefonica Deutschland GmbH
Management of data protection & IT security-related projects. Adjustments to knowledge management and consulting processes.
Activities:
- Data protection consulting
- Process optimization in in-house consulting
- Interface to specialist departments, IT security, development and management
Michael S.
Last position:
Data Analyst, Data Scientist at CompuGroup Medical Deutschland AG, docmetric GmbH
Development of AI and traditional models to analyze medical and patient data, including medication analyses, diagnosis analyses, forecasts, procedure analyses, dosage analyses, comorbidity analyses, prescription analyses, patient potential analyses, referral profile analyses, and prescription analyses. Analyses in the field of Real World Evidence.
Healthcare IT, pharmaceutical industry
Tasks, responsibilities:
- Gathering customer requirements
- Planning the subproject
- Designing and defining KPIs
- Designing and developing models and visualizations of results using customer dashboards
- Developing and implementing data warehouse adaptations
- Deriving recommendations for action
Methods, technologies:
- Simulation
- Artificial intelligence
- Python
- R
- SQL
- Microsoft Power BI
- Amazon Web Services
- Elasticsearch
- PostgreSQL
- Databricks
- Multivariate statistics
Kiriakos K.
Last position:
Tech Lead / Architect : OTTO API Platform at OTTO
Maturing their API practices on both a business and technology level. My role covers 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, Node.js, TypeScript, Redocly, reactive programming, CDC, Golang, Gin, GitOps, DX (developer experience), stakeholder management, roadmaps, workshops, discovery.
Eric B.
Last position:
Quality Assurance Manager (QSV) at Federal Employment Agency
Supporting the International Web Presence of the BA (IntWeb) project in the area of quality management, with the aim of taking responsibility for the quality of processes and project results while considering BA standards. The main objectives of the project are to give professionals abroad a quick overview of their opportunities for moving to Germany and to enable them to take the necessary steps consistently and with digital support by providing access to services.
Defining the general guidelines in the QA handbook
Summarising test results in QA reports for PLA
Analysing project results for improvement opportunities
Quality management of requirements analysis (particularly processes, methods, and tools)
Ensuring compliance with SERA requirements
Creating a cross-project test concept
Agreeing on sprint completion reports
Formal review of work results in accordance with requirements and/or the project plan
Contact person for internal audit, external audits by auditors, or BRH (Federal Court of Audit)
Technologies: JIRA, Confluence, MS Office, GitLab, Kubernetes
Fatiha A.
Last position:
Science Coordinator at Heinrich-Heine-Universität
- Coordinate a large-scale, DFG-funded research project involving 19 interdisciplinary research groups across multiple institutions, including the MibiNext Graduate School
- Lead project governance and stakeholder communication through structured milestone tracking and reporting to university administration
- Organise and coordinate scientific events, including an international symposium and DFG on-site evaluation, managed invitations, participant communication and event-related enquiries
- Website maintenance and content creation
- Editing, formatting, reviewing, and compilation of abstract book and various documents
- Coordinate logistics, communication, scheduling, and stakeholder engagement across participating institutions
Ashwin P.
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.
Anshita S.
Last position:
Business Intelligence Developer and Data Analyst at Deloitte Consulting
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
Bardiya B.
Last position:
Data Scientist at Rewe Digital GmbH
Statistical Forecasting Algorithm
- Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
- Migration from R/On-premise to Python/Snowflake
- Productionalization on Snowflake in cooperation with data engineers & DevOps
Monitoring Dashboard
- Data engineering for preparation & provisioning of necessary data/resources on Snowflake
- Development & deployment of a Streamlit dashboard in Snowflake
ML-based Probabilistic Forecasting on Vertex AI
- Development of a ML-based probabilistic forecasting algorithm from scratch
- Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI
Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow
Philipp G.
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
Alyosh A.
Last position:
Business Intelligence Consultant at Large Private Equity Group
- Business intelligence and KPI specification and playbook for 35 European companies.
Manfred B.
Last position:
Interim Manager Managing Director
- Optimization of business results and expansion of sales activities
- Responsible for personnel organization
- Introduction of a document management system (DMS)
- Introduction and optimization of the ERP, CMS and CRM landscape
- Introduction of digital signatures
- Increase in revenue, reduction in costs and increase in EBIT
Benjamin M.
Last position:
Founder, system architect, and main developer at Institute for Artificial Study (IAS)
- Expert-supervised AI systems for scientific reasoning, model evaluation, and research workflows.
- Built the IAS Problem Solver, an orchestrated system for difficult mathematical reasoning; it achieved 84% in one submitted answer set on the Leipzig mathematics benchmark.
- Built a resumable state-machine pipeline for research-grade mathematics benchmark generation: source selection, LLM-agent-based phenomenon discovery, task synthesis, gold-answer and certificate generation and validation, probing, repair, human feedback, and quality gates, targeting tasks that are difficult, natural, verifiable, and cost-effective.
- Current work extends this into budget-aware AI research workflows for real scientific problems with expert review.
Tech stack: Python, OpenAI/OpenRouter-compatible APIs, embeddings, RAG, SQLite.
Valery K.
Last position:
Sr. Data Scientist & Engineer at Virtual Minds
- 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
Martin E.
Last position:
IREB Requirements Engineer at IREB Germany
- IREB Consultant Requirements Engineer
- IREB Ambassador for the Baltics
Axel K.
Last position:
Data Engineer & Business Analyst at Metafinanz
- 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
Discover over 15,000 top freelancers
Statistics of experts using Data Mining
Aggregated from the professional profiles of matched freelancers.
Experience
22 years
Position duration
2.6 years
Positions per freelancer
14
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Professional Services, Automotive
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
95%
Master's degree or higher
77%
Doctorate
19%
Certifications per freelancer
3
Most common languages
English, German, French
Speak two or more languages
100%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Discover detailed Data Mining rate benchmarks:
Explore rate insightsAverage rates of experts in Germany using Data Mining
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Mining 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 (92%)
- Professional Services (55%)
- Automotive (49%)
- Banking and Finance (48%)
- Manufacturing (38%)
- Media and Entertainment (37%)
- Retail (37%)
- Education (34%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Mining does
Data Mining examines large, varied data sets to discover patterns, relationships and anomalies that support business decisions. It combines statistics, database methods and machine learning to turn raw records into useful findings. Typical outputs include customer segments, forecasts, recommendation logic, fraud signals and process insights.
Typical applications
Companies use it where valuable signals are spread across transactional, behavioral or machine data.
- Customer segmentation and churn analysis
- Fraud, risk and anomaly detection
- Demand forecasting and recommendation models
- Quality monitoring for industrial and supply-chain data
- Text, clickstream and sensor-data analysis
Tools and methods
Professionals work across SQL databases, data warehouses and distributed processing environments. Python libraries such as pandas, scikit-learn and PySpark are common, while R remains useful for statistical analysis and reporting. Strong practice also covers feature engineering, clustering, classification, regression, association rules and model evaluation.
When companies need specialists
Freelance expertise helps when an internal team has data but lacks a clear analytical path, or when a proof of concept must become a dependable production workflow. It is also valuable during warehouse migrations, fraud initiatives, customer analytics programs and the redesign of reporting pipelines. In Germany, projects often combine remote delivery with close coordination across business, IT and compliance teams.
What quality looks like
A strong professional starts with the decision the analysis must support, not with a preferred algorithm. They check data lineage, missing values, bias, leakage and sampling before trusting a result. They explain assumptions clearly, compare useful baselines and deliver reproducible notebooks, tested pipelines, documented features and findings that non-specialists can act on.
Skills beside Data Mining
The work often connects to data engineering, business intelligence, cloud platforms and applied machine learning. Useful adjacent knowledge includes APIs, ETL orchestration, data governance, privacy controls, visualization and experiment design. Look for someone who can move from source-system questions to a validated result and explain how it will be maintained after handover.
Frequently asked questions
Quick answers to the questions that come up most around Data Mining.
Data Mining is used to find meaningful patterns in large data sets and support decisions with evidence. Common applications include churn prediction, fraud detection, customer segmentation, demand planning, recommendations and anomaly monitoring.
Data Mining searches for relationships and signals that may not be known in advance, often using statistical or machine learning methods. Traditional reporting usually summarizes defined measures, while mining can identify hidden segments, unusual behavior or predictive factors.
A strong Data Mining specialist usually understands SQL, data modeling, statistics and data preparation. Python or R, visualization, cloud data services, ETL pipelines and machine learning operations are valuable when findings must become a repeatable business process.
The right level for Data Mining depends on data quality, risk and delivery scope rather than on a fixed time period. A contained exploratory analysis may need a specialist who can work independently, while production scoring, sensitive data or complex integration calls for deeper experience with validation, deployment and governance.
Yes, Data Mining work is often suitable for remote collaboration when data access, documentation and security procedures are prepared. On-site workshops can still help with stakeholder discovery, especially when the project involves operational teams, restricted systems or German-language communication.
Before starting Data Mining, define access rights, data ownership, retention rules and the intended use of the results. The specialist should work with representative samples first, document transformations and coordinate with security and privacy stakeholders where personal or commercially sensitive data is involved.
Good Data Mining work links every finding to a clear business question and shows how the data was prepared. Review validation design, baseline comparisons, error analysis, reproducibility and whether the result remains understandable and useful outside the original analysis.
Data Mining is a broader process of discovering useful patterns, which can include statistical analysis, database queries and machine learning. Machine learning focuses on algorithms that learn from data for tasks such as prediction or classification, so the two areas overlap but are not identical.
The average hourly rate of freelancers in Germany who have used Data Mining in their recent projects is 103 €, which corresponds to a daily rate of about 826 € based on an 8-hour working day.
Of the freelancers in Germany who have used Data Mining in their recent projects, 95% hold at least a Bachelor's degree, 77% hold at least a Master's degree, and 19% hold a doctorate.
On average, freelancers in Germany who have used Data Mining in their recent projects have 22 years of professional experience, with a single engagement typically lasting around 2.6 years.
The most common languages among freelancers in Germany who have used Data Mining in their recent projects are English (100%), German (98%), and French (25%).
The most common industries among freelancers in Germany who have used Data Mining in their recent projects are Information Technology (92%), Professional Services (55%), and Automotive (49%).
The most common business areas among freelancers in Germany who have used Data Mining in their recent projects are Information Technology (91%), Product Development (82%), and Business Intelligence (80%).
Main locations of FRATCH Experts, who have recently used Data Mining
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
