Data Science Experts in Munich
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Meet FRATCH Experts in Munich, who have recently used Data Science
Kai Z.
Last position:
Enterprise Program Manager / Program Lead at YouGov Consumer Panel Services
The program supports the comprehensive realignment of the German Consumer Panel Services business. It combines a significant panel boost with the reprocessing of historical data and the integration of new receipt data. By significantly expanding and stabilizing the panel with the involvement of external partners, the aim is to improve the validity of the data base and create a reliable foundation for methodology, weighting and customer reporting. At the same time, historically grown processes for data delivery, OCR, matching, item QC, methodology and reporting are being harmonized, further developed technologically and reorganized. The goal is a scalable end-to-end landscape with higher data quality, clear responsibilities, reliable governance and sustainably manageable operational processes.
- Overall management of the restatement program, including the integrated roadmap as well as milestones, dependencies, risks and management decisions.
- Coordination of the panel boost and alignment of the required data deliveries, quality requirements and prerequisites for methodology, weighting and reporting.
- Alignment of business, product, data science, technology, operations and external partners around a shared target picture, aligned priorities and an integrated approach.
- Design of the organizational change triggered by the fundamental realignment of the data base, methodology and management logic, which has a lasting impact on established decision-making and collaboration patterns.
- Establishment and further development of governance, reporting and escalation structures as well as program-wide monitoring and operational processes for reliable management and sustainable handover.
- Management of critical data, technology and provider dependencies, including reprocessing, OCR transition and the timely synchronization of delivery, testing, methodology and reporting.
- Orchestration of international collaboration with teams and stakeholders in Germany, the United Kingdom, Portugal and Romania, as well as with external suppliers in Germany and Austria.
Impact Areas and Expertise: Program & Delivery Leadership, Business & Technology Alignment, Organization & Transformation, Governance & Sustainable Operations, Strategy & Target, Methodic Leadership, Transformation & Change Leadership, Executive Advisory
Uwe C.
Last position:
CEO at Cohrs Consulting & Coaching
GTM Services
As a coach, mentor, salesperson, networker and project manager, I support individuals and organizations in achieving their goals.
Michael N.
Last position:
Senior AI Engineer | Forward Deployed Engineer at Tiefbau
- Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
- Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
- Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.
Mirza K.
Last position:
Agentic Automation and a RAG system
- This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.
Used: Python, RAG, LangGraph, LangChain, deepeval, MCP
Natalya P.
Last position:
Prioritisation, Sequencing and Operating Model at a-connect client, Fortune 500 life sciences and agriculture group
Prioritisation, Sequencing and Operating Model
a-connect client, Fortune 500 life sciences and agriculture group
- Consolidated competing business needs across five businesses into one prioritised agenda: assessed 1,000+ services against value, readiness and feasibility, weighed options, trade-offs and dependencies, and recommended the sequence of work, including what had to be redesigned or stopped before anything moved. Published case study.
- Aligned business, technology and data stakeholders on priorities and decisions across five businesses with separate leadership, P&Ls and competing agendas, onto one roadmap and six shared decision principles, without formal authority over any of them.
- Translated business intent into delivery-ready requirements and readiness standards that engineering, data and architecture teams could act on, with gates that stopped anything reaching production before the process, data and accountability behind it were fit.
- Established the sustainable prioritisation and progress-tracking approach the organisation still runs: service ownership, decision rights, escalation routes, governance forums and measurement, converted into a repeatable method that later teams operate without the author in the room.
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
Tandi T.
Last position:
Founder, Circular Business Advisor at Circular Business Network
First network for professionals working on circular business models
Founded a global network for professionals working on circular business models to connect, collaborate, innovate, and scale impact.
- Partnered with the City of Munich and Circular Munich on a 3-year strategy to improve data collection and textile reuse in Munich.
- Advised 5 SMEs on how to pilot, scale and optimize circular business models for profitability and sustainability.
- Produced market research on the circular business landscape to highlight opportunities, trends and risks.
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
Any-Arlene N.
Last position:
Co-Founder · Data Engineering & Backend at zirikana (Kirundi Bible Web App) – Civic Technology
- Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
- Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
- Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
- Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.
Omar A.
Last position:
Senior Fullstack AI Engineer (Team Lead – B2C Platform) at mama health
- Partner directly with C-level leadership (CEO, CAIO, CTO) on architecture, OKR strategy, and cross-team roadmap prioritization, translating strategic goals into structured engineering requirements.
- Surfaced and mapped technical debt across the entire organization with C-level leadership and co-defined a prioritized remediation strategy, balancing debt paydown against feature delivery.
- Led code reviews and technical standards across the team, fostering a mentor-first environment with two-way feedback dialogue — pairing on complex pipeline work and unblocking junior engineers on async architecture patterns.
- Re-architected the AI companion's core processing pipeline from synchronous to asynchronous with a queue-based worker architecture, enabling horizontal scalability and cutting upload processing time ~4x (from ~22s to 5–10s) while improving response accuracy.
- Designed an AI-driven document intelligence workflow with automatic multi-document classification, per-document summarization, and relevance guardrails for the patient care journey.
- Built a unified patient memory system (short- and long-term context) bridging the document vault and chatbot into a single bidirectional, context-aware platform.
Serge K.
Last position:
Data Scientist & MLOps (Machine Learning Operations) at REWE Digital GmbH
- It is like a startup within REWE, where we have to build a new forecasting system on Google Cloud Platform from the scratch. Although, officially my role is called MLOps, my actual tasks also include development of data processing pipelines (data engineering) and data scientists tasks such as feature engineering and model trainings.
- GCP: Terraform (tofu), Vertex AI (Kubeflow), Cloud Run, IAM, Google Cloud Storage, BigQuery, Artifact Registry
- Data engineering: Snowflake as the main data warehouse, Terraform, DBT for data model implementations
- CI/CD: GitLab. We have built a CI/CD pipeline that automates deployments of new releases up to production environment
- Development of feature store and data synchronization between environments
- Data science: evaluation of different forecasting models, including CatBoost, Contextual Gamma and Random Forest; implementation of training pipelines using Kubeflow on Vertex AI; scaling and development of an event-driven interface using Kafka as a forecasting service; evaluation of MLFlow for model tracking and model registry
- Implementation of REST API using KeyCloak OAuth2 and OpenID (JWT)
- Monitoring: implementation of dashboards with Grafana, Prometheus, Mimir, Streamlit and Loki to monitor prediction metrics, GCP and Snowflake costs for pipelines, and system metrics
- Development of Copilot Agent Skills
Vitaliy R.
Last position:
DevOps GitOps (temp) at Signal Iduna
- Responsible for Openshift/Kubernetes on-prem administration and developer support.
- Developed URP infrastructure automation with Python, Ansible, Kustomize and ArgoCD, Argo Workflow/Events stack.
- Wrote smoke and load tests for URP infrastructure utilizing Python, Kustomize and ApplicationSets.
- Helped to set up and deploy URP infrastructure in Google Cloud, GKE.
- Set up monitoring for URP and ArgoCD stack with Splunk Cloud.
- Performed system administration tasks across RedHat Linux, Kubernetes/Openshift, ArgoCD, GitLab, Bitbucket Enterprise, Kafka and MongoDB.
David T.
Last position:
AI Trainer (NLP & LLM Evaluation) at Freelance
- Designed and evaluated high-quality prompts and completions for Large Language Models (LLMs), focusing on improving response accuracy, instruction-following behavior, and factual consistency.
- Annotated and rated LLM-generated outputs for grammar, coherence, relevance, and truthfulness.
- Developed RLHF-style preference data by ranking model completions to inform reinforcement learning fine-tuning cycles.
- Participated in prompt engineering experiments to assess the effect of instruction format, verbosity, and phrasing on model behavior.
- Conducted error analysis and quality assurance on large-scale NLP datasets, identifying edge cases and linguistic ambiguity affecting LLM performance.
Stephan B.
Last position:
Freelance Data Scientist at Baier Data & AI Consulting
Christiane N.
Last position:
Management Consultant at Christiane Neher Management Consulting
Large Insurance Company – Consultant Wiesbaden: Consulting support for the introduction of an integrated planning and performance management framework (operational, financial, customer) to enhance customer-centric transparency, decision-making quality, and steering capabilities across all lines of business within an insurance organization:
- Analysis of existing processes, reports, KPIs, and KPI calculation methodologies
- Design and introduction of new, standardized customer KPIs (gross/net), as well as key steering metrics with consistent linkage across all lines of business
- Recalculation, validation, and plausibility checks of KPIs based on existing and newly integrated data sources
- Conceptual support for the development of an integrated reporting and performance management setup
- Execution of customer insights analyses to identify patterns and anomalies within customer data clusters
Large retail company – Consultant in Karlsruhe: Advisory services for the setup and step-by-step implementation of an internationally deployable RELEX solution in the supply chain management environment:
- Advising overall and sub-project management on methodology, project setup and steering (e.g. agile approach, Jira configuration, RELEX phases, Jira Structure PPM)
- Strategic-operational consulting for the introduction of RELEX including best practices
- Support in defining overarching goals and requirements (2-year target picture)
- Guidance in scoping a relevant supply chain network segment for the project
- Development of a roadmap for iterative, incremental RELEX setup and rollout
- Assessment of project dependencies (interfaces, configurations, etc.)
- Advice on prioritized implementation of business requirements and data interfaces
- Support in test planning (data validation, system testing, UAT)
- Consulting on internationalization, change management, training, and knowledge transfer
- Stakeholder advisory and alignment activities between the client, implementation partner, and RELEX
Insurance company – Management Consultant in Munich: Analysis, consulting and support for the optimization of a large-scale business and IT transformation. Focus on strategically important programs and modernization projects in the area of Managed Services Operations and processes:
- Review of project plans and deliverables; analysis of programs and projects (e.g. cloud approach, process standardization, system integration, roadmaps)
- Identification of technical, functional and personnel risks and challenges; development of content-related measures and alternative solutions
- Proposal of quality improvements for program and modernization efforts
- Sparring partner and professional, technical, structural and organizational consulting for project and program management
Large retail group – Management Consultant & Stream Lead in Cologne: Consulting, process, project and product management for the introduction and implementation of a large strategic program in the field of advanced analytics, assortment and space management:
- Setup, test and rollout of a new space planning, automation and optimization product based on the existing cluster-based merchandising approach
- Definition and setup of new processes and transformation and change management measures for the new store-specific merchandising approach
- Collaboration with Advanced Analytics and IT (internal and external) for software implementations, automations, extensions and interfaces
- MVP approach and piloting in phases with gradual rollout (pilot with 80 stores, region with 500 stores, national level with 4000 stores)
Large retail company – Agile Coach & Change Agent in Cologne: Agile coach, OKR master and facilitator for the introduction of the OKR approach in a large strategic digitization program for retail stores:
- Coaching of the core team with topic managers and team leads
- Introduction to the OKR topic and setup of the OKR cycle
- Establishment of the OKR approach in teams and on a cross-team level
Delivery and logistics company – Management Consultant in United Kingdom: Consulting and coaching in the restructuring of the Data Analytics department:
- Analysis of current challenges
- Definition of overarching goals
- Development of a proposal for a new team structure
- Identification of required competencies, skills and responsibilities
- Advisory and alignment on communication and change management strategy
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
16 years (Germany: 14 years)
Position duration
2.2 years
Positions per freelancer
10 (Germany: 9)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
86% (Germany: 80%)
Doctorate
23% (Germany: 22%)
Certifications per freelancer
3
Most common languages
English, German, Spanish
Speak two or more languages
100% (Germany: 97%)
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 Munich 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.
Average rates of experts in Munich 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 29 Oct 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 (87%)
- Banking and Finance (49%)
- Professional Services (47%)
- Education (43%)
- Automotive (36%)
- Manufacturing (36%)
- Media and Entertainment (36%)
- Retail (36%)
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. Specialists build forecasting models, customer segmentation, recommendation systems, anomaly detection and analytical products. They work across structured records, text, images, sensor data and event streams.
Core methods and outputs
A strong project starts with a clear business question and dependable data. Specialists explore sources, define useful features, select suitable models and validate results against real operating conditions. Typical deliverables include:
- Data quality checks and exploratory analysis
- Forecasting and classification models
- Recommendation and ranking systems
- Interactive reports and decision dashboards
- Reproducible notebooks, documentation and handover material
Ecosystem and tooling
Python is central to many Data Science projects, with pandas, NumPy, scikit-learn, PyTorch and TensorFlow supporting analysis and machine learning. SQL, Spark and cloud services help process larger datasets, while tools such as MLflow, Docker, Git and orchestration workflows support repeatable delivery. The right stack depends on data volume, latency, security and the way results will be used.
When companies bring in specialists
Companies often seek freelance expertise when internal teams have valuable data but lack the capacity to turn it into a working solution. This is common during a new product launch, a move from analysis to production, a model review or a modernization of reporting and data pipelines. In Munich, specialists may support automotive, manufacturing, finance, healthcare, retail and technology organizations, remotely or in close collaboration with local teams.
What strong professionals do differently
Strong professionals connect model quality with business impact. They challenge weak assumptions, check for leakage and bias, explain trade-offs clearly and choose a simpler approach when it is more reliable. They also understand deployment, monitoring, data governance and maintenance rather than stopping at a promising notebook. Clear communication in English is common in international teams; German can matter for local stakeholders and regulated work.
How to assess the fit
Look for evidence that a specialist has taken a project from messy source data to a usable outcome. Ask how they define success, validate models, handle changing data and communicate uncertainty. Relevant adjacent skills may include data engineering, software development, cloud architecture, product analytics, visualization and domain research. A focused trial or technical review can reveal whether the professional fits your data, constraints and decision process.
Frequently asked questions
What clients ask us most about Data Science — answered in short.
Data Science helps companies find patterns in data and use them to support decisions or automate actions. Common applications include demand forecasting, fraud detection, churn analysis, personalization, quality control and operational optimization.
Data Science usually goes beyond reporting past performance by using statistical modeling, experimentation and machine learning to explain outcomes or predict what may happen next. Business intelligence often focuses on trusted dashboards, recurring reports and interactive analysis.
A strong Data Science specialist may also work with SQL, data engineering, cloud services, software development and data visualization. Product thinking, domain knowledge and clear communication are equally important when models must influence real decisions.
The right Data Science experience depends on the risk, data quality and production demands of the project. A forecasting prototype may need a different profile from a regulated machine-learning service that requires monitoring, explainability and robust deployment.
Data Science work is often well suited to remote collaboration because data, notebooks, repositories and cloud environments can be shared securely. On-site sessions in Munich can still help with stakeholder workshops, domain discovery, access controls and close work with local teams.
Before engaging a Data Science freelancer, define access rules, data ownership, retention requirements and the permitted use of sensitive information. A clear environment, documented interfaces and appropriate security review reduce risk without blocking useful analysis.
Evaluate how a Data Science professional frames the problem, tests assumptions and measures performance against a meaningful baseline. Good specialists explain uncertainty, investigate bias and leakage, document their work and show how the result will be maintained after delivery.
Data Science does not always require machine learning. If a rule, statistical method, well-designed experiment or simple dashboard answers the question more transparently, a specialist should be willing to recommend that option instead.
The average hourly rate of freelancers in Munich, Germany who have used Data Science in their recent projects is 103 €, which corresponds to a daily rate of about 824 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 86% hold at least a Master's degree, and 23% hold a doctorate.
On average, freelancers in Munich, Germany who have used Data Science in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Munich, Germany who have used Data Science in their recent projects are English (100%), German (94%), and Spanish (26%).
The most common industries among freelancers in Munich, Germany who have used Data Science in their recent projects are Information Technology (87%), Banking and Finance (49%), and Professional Services (47%).
The most common business areas among freelancers in Munich, Germany who have used Data Science in their recent projects are Information Technology (89%), Product Development (81%), and Business Intelligence (79%).
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 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Nuremberg Request a free demo
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FRATCH CEO
