Matplotlib Expert in Berlin
for clear data stories, matched in minutes with vetted, available freelancersHire experts who turn Python data into accurate, publication-ready charts, dashboards and analytical visuals with Matplotlib, NumPy and pandas. Get fast, precise matching with vetted, available freelancers for remote or on-site work in Berlin.
Meet FRATCH Experts in Berlin, who have recently used Matplotlib
Wolfram K.
Last position:
AI / Machine Learning Engineer (Projects & Applied AI) at UNIVERSITÉ PARIS 1 PANTHEON-SORBONNE & LIORA
- Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
- Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
- Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
- Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
- Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow
Santina W.
Last position:
Business Analyst & BI Strategist - Comparison Portal at dataweys (self-employed)
- Assessment of the existing reporting landscape and strategic bundling of needs
- Migration and consolidation of reports to Metabase, connected to ClickHouse as the data foundation
- Building and maintaining data pipelines
Stack: Metabase · ClickHouse · Appsmith · Airflow
Tobias J.
Last position:
Design of an AI-Agent-Based ERP System
- Design of an LLM-based agent system to control the ERP software
- Development of agent workflows with LangGraph and PydanticAI
- Planning interfaces between business logic and language models
- Planning agent orchestration
- Prototype development and demonstration
Tools: Python, Pydantic, React, LangChain, LangGraph, Linux
Tushar R.
Last position:
Research Assistant/Master Thesis at Otto-von-Guericke Universität Magdeburg
- Performed qualitative and quantitative analysis of extracted findings, categorizing themes, evaluating methodologies, and assessing study quality and reliability.
- Produced research reports and evidence summaries communicating key trends, gaps, and opportunities to academic advisors or cross-functional teams.
- Presented findings through well-structured visualizations, tables, and narrative summaries to support decision-making and guide future research directions.
Phil H.
Last position:
Data Analyst at Applied Analytics Projects
- Designed and implemented end-to-end data workflows (BigQuery + PowerBI), transforming raw datasets into executive dashboards used for KPI monitoring
- Queried and transformed large-scale datasets using Google BigQuery to support analytical use cases and insight generation
Deependra P.
Last position:
Data Specialist at Cloud Factory
- As a Data Specialist, I leveraged analytical expertise to transform raw data into actionable insights, driving strategic decision-making and operational improvements. My role encompassed data interpretation, reporting automation, and cross-functional collaboration, utilizing advanced tools such as Microsoft Excel, Power BI, and Python for comprehensive data analysis.
- Implemented Python scripts to validate and reconcile large datasets, reducing manual errors and improving data reliability.
- Utilized Python (Pandas, NumPy, Matplotlib/Seaborn) to automate data cleaning, analysis, and visualization, improving efficiency and accuracy in reporting.
- Developed interactive dashboards in Power BI to present key metrics, trends, and performance indicators, facilitating real-time decision-making.
- Designed and executed automated reports using Excel (Pivot Tables, Power Query, VBA) and Power BI, ensuring data accuracy and consistency across departments.
- Data Analysis: Excel (Advanced Pivot Tables, Power Query), Power BI (DAX, Data Modeling), Python (Pandas, NumPy, Visualization Libraries)
- Automation & Reporting: Power BI Dashboards, Excel Macros (VBA), Python Scripting.
Sebastian P.
Last position:
Postdoctoral Research Associate at Max Planck Institute for Human Development
- Published a peer-reviewed article on comparative analysis of biophysical models in diffusion MRI, impacting ongoing research projects.
- Got SciPy selected for the cover image of the corresponding journal issue.
Philipp G.
Last position:
Machine Learning Engineer at docmetric GmbH
- Analyzed patient data for various clients
- Developed complex analysis pipelines
- Performed quality assurance on methods
Srikar K.
Last position:
Application Developer at Vavili Technologies
- Played a key role in developing templeswiki.com as a Full Stack Developer, building and optimizing multiple pages and microservices to ensure a responsive and user-friendly experience.
- Developed an interactive chatbot integrated with Natural Language Processing (NLP) to enhance user engagement and streamline customer interactions within the application.
- Built a robust ETL pipeline using Python to generate multi-language labels, facilitating seamless content translation across languages.
- Led the QA team by crafting a comprehensive test plan to rigorously test and ensure the application's smooth operation, alongside developing an in-house attendance recording tool to improve organizational efficiency.
Kashaf K.
Last position:
AI Consultant / Expert at Siemens Mobility
- Evaluated 45+ AI use cases and developed a prioritization framework for Siemens’ internal AI roadmap.
- Tested internal tools like DRIM, SiemensGPT, Microsoft Copilot; presented evaluation outcomes to stakeholders.
- Identified performance gaps and improved tool adoption by 65%.
- Supported AI knowledge-sharing initiatives, led tool onboarding sessions, and improved team AI literacy.
- Collaborated with engineering, procurement, and digital teams on tool feedback and strategy alignment.
Vignesh T.
Last position:
Shift Lead at Flink Expansion GmbH
- Analyzed operational data from 400+ daily orders to identify bottlenecks and optimize delivery workflows, achieving 97% on-time delivery rate through data driven process improvements.
- Led cross-functional team of 10+ associates using data insights to improve protocol adherence by 25% and boost productivity by 15% within 3 months.
- Implemented performance tracking dashboards and KPI monitoring systems that improved staff retention by 10% and maintained 100% safety compliance.
- Drove operational excellence through continuous A/B testing of workflow processes and real-time performance analytics.
Ege P.
Last position:
AI Research Collaborator at NPO
- Contributed to the Karakutu project, developing AI-driven tools to analyze news in Turkey.
- Assisted in web scraping, applied NER for entity extraction, and built interactive filtering interfaces (Vue.js, Plotly.js) for entity and location based search.
- Performed sentiment and content-shift analysis to detect editorial influence in modified news articles.
Maurizio F.
Last position:
Python Software Developer at Schönhofer Sales and Engineering GmbH
- Implemented a command line interface (CLI) for integration of REST APIs of various microservices for end users
- Centralized and simplified interaction with services through the CLI
- Implemented a REST microservice for custom data schemas based on an API-first approach
- Developed event-driven control with RabbitMQ to connect to other services
- Deployed services using Docker and Kubernetes and extended the CLI
- Managed complexity and data volume handling through the microservice
Shyam Sundar R.
Last position:
GenAI Engineer at Freelance
- Built a hybrid semantic and keyword search and LLM-based requirement extraction from conversational queries, boosting search accuracy by 85%, cutting zero-result searches by 70%, and reducing search time by 60%.
- Deployed a production-ready API with monitoring dashboards over 100K+ products, keeping response times under 2s and reducing customer search-to-purchase time by 40%.
- Technologies: Python, BGE-M3, Qwen2.5, FastAPI, Qdrant, Meilisearch, Docker, Prometheus, vLLM.
Manasvi K.
Last position:
Max-Cut with MQT-Quantum Auto Optimizer (QAOA vs Classical Baseline) at Independent Project
- Formulated Max-Cut as a QUBO and implemented QAOA vs a Simulated Annealing baseline with reproducible parameter sweeps, fixed seeds, and exact checks on small graphs
- Verified both approaches reached the known optimum on all tested instances; deeper QAOA increased runtime with limited gains on these cases
- Tech: Python · mqt.qao · Qiskit · qiskit-algorithms · NetworkX · Matplotlib · NumPy · SymPy
Discover over 15,000 top freelancers
Statistics of experts using Matplotlib
Aggregated from the professional profiles of matched freelancers.
Experience
11 years
Position duration
1.9 years (Germany: 2 years)
Positions per freelancer
7
Top business areas
Information Technology, Research and Development, Business Intelligence
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Business Intelligence, Information Technology, Research and Development
Bachelor's degree or higher
100%
Master's degree or higher
89% (Germany: 85%)
Doctorate
16% (Germany: 19%)
Certifications per freelancer
2
Most common languages
German, English, Hindi
Speak two or more languages
95% (Germany: 98%)
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 Berlin 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 Berlin using Matplotlib
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.
Matplotlib 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 (80%)
- Education (55%)
- Healthcare (40%)
- Government and Administration (30%)
- Manufacturing (25%)
- Media and Entertainment (25%)
- Professional Services (25%)
- Transportation (20%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Matplotlib does
Matplotlib is a Python library for creating charts, plots and publication-quality figures from data. Its pyplot interface supports common visualisations, while the object-oriented API gives teams precise control over axes, labels, annotations, legends and layout. It fits notebooks, scripts, reports and production workflows.
Typical deliverables
- Exploratory plots for data analysis and model review
- Line, bar, scatter, histogram and heatmap visualisations
- Multi-panel figures with shared axes and annotations
- Export-ready charts for reports, presentations and publications
- Reusable plotting functions and visual style systems
Matplotlib can turn raw analytical output into visuals that support decisions. Strong implementations make the result readable as well as technically correct.
Ecosystem and tooling
Matplotlib works closely with Python data tools such as NumPy, pandas and SciPy. Experts may also use Jupyter, Seaborn, Plotly or GeoPandas when a project needs interactive views, statistical styling or geospatial context. They typically manage figure sizing, colour maps, fonts, backends, file formats and rendering behaviour across environments.
When companies need help
Companies often bring in freelance expertise when existing charts are inconsistent, slow to maintain or difficult to interpret. Support is useful during analytics migrations, research delivery, reporting redesigns and the preparation of figures for regulated or technical audiences. Berlin teams may value specialists who can combine remote delivery with clear local collaboration in English or German.
What strong specialists deliver
A strong Matplotlib professional understands both the data and the audience. They check aggregation logic, scales, units, missing values and visual encodings before polishing the figure. They build reusable functions instead of one-off notebook output, document assumptions and keep charts accessible across screen, print and export formats.
Quality checks that matter
- Axes, units, labels and legends communicate without guesswork
- Colours remain meaningful in print and for colour-vision differences
- Figures render consistently across notebooks, scripts and CI jobs
- Layouts avoid clipped text, overlap and misleading scale choices
- Source data and transformation steps can be traced and tested
When assessing a specialist, review an example close to your use case. Ask how they validate a chart, separate plotting logic from business logic and choose between static and interactive output. The best work is reproducible, honest about uncertainty and easy for another professional to extend.
Frequently asked questions
What clients ask us most about Matplotlib — answered in short.
Matplotlib is used to create static charts for analysis, reporting, scientific communication and quality checks. It can support anything from a quick notebook plot to a reusable visualisation component in a Python application.
Matplotlib provides detailed control over figure structure, styling and output formats. Seaborn adds a higher-level statistical interface on top of it, while Plotly focuses more on interactive charts, so the right choice depends on the audience and delivery format.
A strong Matplotlib specialist usually understands Python, NumPy, pandas and data cleaning. Experience with Jupyter, statistical reasoning, colour design, file export and testing also helps when charts must be reliable and reusable.
A small charting task may need someone comfortable with Matplotlib fundamentals and the project data. A reporting system or scientific workflow calls for deeper skill in reusable APIs, visual validation, performance, accessibility and integration with the surrounding Python stack.
Matplotlib projects are well suited to remote work because figures, notebooks and Python modules can be reviewed through version control. Clear requirements, shared data samples and documented rendering environments matter more than physical proximity, while German or English communication can support Berlin-based teams.
Matplotlib is primarily designed for static visual output, although interactive inspection is possible in notebooks and supported environments. For browser-based dashboards, a specialist may combine it with another tool or recommend Plotly, depending on the interaction requirements.
Review whether Matplotlib figures are accurate, readable and reproducible, not just visually attractive. Ask the specialist to explain data transformations, scale choices, edge cases, export settings and how another team member would maintain the plotting code.
Matplotlib supports high-quality raster and vector exports, custom fonts, controlled dimensions and detailed layout settings. A capable specialist will also test the final files at their intended size and check labels, line weights, colour use and embedded fonts.
The average hourly rate of freelancers in Berlin, Germany who have used Matplotlib in their recent projects is 72 €, which corresponds to a daily rate of about 580 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Matplotlib in their recent projects, 100% hold at least a Bachelor's degree, 89% hold at least a Master's degree, and 16% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Matplotlib in their recent projects have 11 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Berlin, Germany who have used Matplotlib in their recent projects are German (100%), English (95%), and Hindi (20%).
The most common industries among freelancers in Berlin, Germany who have used Matplotlib in their recent projects are Information Technology (80%), Education (55%), and Healthcare (40%).
The most common business areas among freelancers in Berlin, Germany who have used Matplotlib in their recent projects are Information Technology (85%), Research and Development (70%), and Business Intelligence (65%).
Main locations of FRATCH Experts, who have recently used Matplotlib
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.
Hamburg 
Munich 
Frankfurt 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
