Data Science Experts in Dusseldorf
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Meet FRATCH Experts in Dusseldorf, who have recently used Data Science
Stephan S.
Last position:
Head of Digital Transformation EMEA at Rhenus Air & Ocean Management GmbH
Responsible for driving digital transformation and aligning country organizations with the Rhenus platform model
Initiated the digital transformation roadmap for five countries, ensuring alignment with global group strategy
Built and led a high-performing digital transformation consulting team, expanding delivery capacity from one to three value streams and thereby fast tracking the roadmap from 3 to 2 years
Acted as strategic advocate for 5 country organizations, ensuring group-wide cross-functional alignment
Redefined business analysis into an agile approach, reducing time-to-value for platform harmonization by 50%
Ehsan A.
Last position:
Clinical Data Scientist at Freelance
- Conduct data management and statistical analysis for clinical studies on behalf of CROs.
- Guest lecturer at Ivancity University, Paris, specializing in data anonymization techniques and statistical disclosure control.
- Provide scientific and medical writing services for pharmaceutical companies.
- Perform optical mapping data analysis and develop software tools with a focus on algorithm optimization and technical support.
Amir F.
Last position:
Senior Project Manager – Data, AI & Digital Transformation I Customer Delivery at Independent / Fortune 500 Clients
- Led AI programs and data initiatives, from PoC/ MVP to rollout, ensuring operational readiness, governance and business adoption.
- Established pragmatic AI governance frameworks enabling compliant and scalable AI delivery.
- Partnered with data science, engineering, and product teams to deliver AI-enabled solutions on enterprise-scale data platforms.
- Defined delivery KPIs and success metrics to ensure measurable business value.
- Led cross-functional, multi-site teams in complex, first-time project environments, managing risks, dependencies, and stakeholder expectations.
- Supported solution scoping and effort estimation in collaboration with consulting and delivery teams.
Marin N.
Last position:
Project Management & Requirements Management | Leadership Consulting at Continental AG
- Project leadership of a cross-functional team of data scientists, software architects, and business stakeholders to develop a dynamic pricing model for the EMEA and US truck tire market
- Management consulting for applied analytics and AI, focusing on agile organizational strategy and designing a global strategy implementation based on agile frameworks with an emphasis on AI enablement
- Methods and technologies used: portfolio management, value stream mapping, SAFe, Scrum, Kanban, Flight Levels, lean management, OKRs, usability testing, acceptance tests, test management oversight
Aziz A.
Last position:
Senior Data Scientist & AI Engineer Consultant at Lialab SAS
- At Groupama: Developed multiple chatbots using Retrieval-Augmented Generation (RAG) to optimize internal processes and customer communication.
- At PwC: Set up an AI lab and developed various AI use cases.
- At La Poste: Analyzed and improved data quality in the data lake.
- At ARTE TV: Built a recommendation system using NLP for better content discovery.
Yasaman N.
Last position:
Research Data Scientist at RWTH Aachen University
- Led large-scale data analysis on high-volume event data, applying statistical modeling and time-series methods to detect weak signals in noisy environments
- Designed and maintained scalable Python data pipelines for real and simulated datasets, optimizing signal detection and background estimation at scale
- Applied advanced statistical inference techniques (likelihood-based modeling, hypothesis testing) to support quantitative decision-making
- Deployed data-processing workflows on HPC clusters using Slurm, enabling parallelized analysis and large-scale batch execution
- Built reproducible, version-controlled data workflows using Python, Bash, and Git to ensure reliability and traceability of results
- Translated complex experimental data into actionable insights, enabling quantitative decision-making
Ehsan M.
Last position:
BI Developer at Telecommunications Infrastructure
- Gather and analyze requirements in close collaboration with business units to develop data-driven solutions and scalable PowerBI reporting infrastructures.
- Perform detailed debugging and optimize existing semantic and data models to ensure a robust data architecture, high data quality, and improved PowerBI reporting.
- Design and implement scalable ETL processes for data preparation and integration.
- Create a wiki for table and view descriptions as well as PowerBI PowerQuery and KPI documentation to ensure a consistent understanding of data structures and metrics.
Sara W.
Last position:
Recruiting & Employer Branding Data Specialist at Sipgate
- Managed the entire hiring process with a focus on data-driven decision-making.
- Analyzed recruiting data using Excel and ATS to optimize processes effectively.
Steffen H.
Last position:
Coordinator IT-Controlling & Purchasing at Fiege Logistik Stiftung & Co. KG
- Agile work in IT controlling and purchasing, including a project to build IT procurement structures
- Month-end closing including forecast, budget creation including calculation of IT service specifications, ad-hoc analyses
- Preparation and defense of business cases, top management reporting, commercial evaluation of new IT demands and contracts
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
13 years (Germany: 14 years)
Position duration
1.9 years (Germany: 2.2 years)
Positions per freelancer
7 (Germany: 9)
Top business areas
Business Intelligence, Information Technology, Product Development
Top industries
Banking and Finance, Professional Services, Education
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
100% (Germany: 80%)
Doctorate
14% (Germany: 22%)
Certifications per freelancer
4 (Germany: 3)
Most common languages
German, English, Persian
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 Dusseldorf 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 Dusseldorf 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.
- Banking and Finance (44%)
- Professional Services (44%)
- Education (33%)
- Energy (33%)
- Information Technology (33%)
- Transportation (33%)
- Manufacturing (33%)
- Food and Beverage (22%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Data Science covers
Data Science combines statistics, programming and domain knowledge to extract useful answers from structured and unstructured data. It supports forecasting, classification, recommendation, anomaly detection and experimentation. Strong work connects technical analysis with a clear business decision.
What it builds
Companies use Data Science to improve products, operations and customer experiences. Typical deliverables include:
- Demand, revenue and capacity forecasts
- Churn, fraud and risk models
- Recommendation and ranking systems
- Customer segmentation and experimentation frameworks
Ecosystem and tooling
Python is common for data preparation and modeling, with pandas, NumPy, scikit-learn and notebooks used across many projects. Specialists may also work with PyTorch, TensorFlow, Spark, SQL warehouses and cloud services. Production work adds APIs, orchestration, version control, monitoring and reproducible pipelines.
When companies need specialists
Freelance expertise helps when internal teams lack a specific modeling skill, need an independent review or must move from a promising analysis to a dependable service. It is valuable during data strategy work, model selection, proof-of-concept delivery and production handover. In Dusseldorf, remote collaboration can support local teams across retail, manufacturing, logistics, finance and healthcare while on-site workshops remain useful for discovery.
What strong professionals deliver
Experienced specialists define the target variable, test data quality and choose evaluation methods that reflect the real business cost of errors. They explain assumptions, uncertainty and limitations instead of presenting a model as a black box. They also document feature logic, create repeatable workflows and consider privacy, security, fairness and model drift.
How projects succeed
A sound engagement starts with a precise question, accessible data and an agreed definition of success. The right professional can challenge weak assumptions, communicate with technical and non-technical stakeholders and leave behind maintainable code and documentation. Clear German or English communication may matter when Dusseldorf-based teams, international stakeholders and distributed specialists work together.
Frequently asked questions
The facts hiring teams ask for most often when it comes to Data Science.
Data Science is used to discover patterns, predict outcomes and support decisions with data. Common applications include demand forecasting, fraud detection, customer segmentation, recommendations, quality control and process optimization.
Data Science often goes beyond reporting historical performance by using statistical modeling, machine learning and experimentation to estimate what may happen next. Business intelligence focuses more on trusted reporting and dashboards, while the boundaries can overlap in modern data teams.
A strong Data Science specialist may also work confidently with SQL, data modeling, cloud warehouses, software development and data visualization. Depending on the project, MLOps, domain expertise, experiment design and responsible AI practices are equally important.
The right level for Data Science depends on the risk, data maturity and delivery stage. An exploratory analysis may need focused analytical expertise, while a regulated or customer-facing model calls for proven production work, careful validation and strong documentation.
Data Science is often well suited to remote collaboration because data, code and experiments can be shared through secure environments. Dusseldorf-based teams may still benefit from on-site workshops for problem definition, stakeholder interviews and handover, with language needs agreed at the start.
Good Data Science work has a clear objective, defensible data preparation and evaluation that matches real-world use. Reviewers should look for leakage checks, sensible baselines, explainable assumptions, reproducible code and evidence that the result can be maintained after delivery.
A Data Science specialist should compare machine learning with rules, statistical models and straightforward reporting rather than assume complexity is better. A simpler approach may be preferable when data is limited, transparency is essential or the expected gain does not justify additional operational effort.
A Data Science engagement may involve clarifying the business question, auditing data, building a prototype, validating results and preparing a model for use. Specialists should expect collaboration with product, domain, data platform and security stakeholders, not isolated work on algorithms alone.
The average hourly rate of freelancers in Dusseldorf, Germany who have used Data Science in their recent projects is 98 €, which corresponds to a daily rate of about 780 € based on an 8-hour working day.
Of the freelancers in Dusseldorf, Germany who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 100% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Dusseldorf, Germany who have used Data Science in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Dusseldorf, Germany who have used Data Science in their recent projects are German (100%), English (100%), and Persian (44%).
The most common industries among freelancers in Dusseldorf, Germany who have used Data Science in their recent projects are Banking and Finance (44%), Professional Services (44%), and Education (33%).
The most common business areas among freelancers in Dusseldorf, Germany who have used Data Science in their recent projects are Business Intelligence (67%), Information Technology (56%), and Product Development (56%).
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 
Cologne 
Frankfurt 
Stuttgart 
Nuremberg Request a free demo
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FRATCH CEO
