Matplotlib Experts in Nuremberg
in minutes from over 15,000 CVs with the power of AIHire experts who create clear Matplotlib charts, refine publication-ready figures, and wire plotting into Python data workflows. Get fast, precise matching with vetted, available freelancers who can work remotely or on site in Nuremberg when needed.
Meet FRATCH Experts in Nuremberg, who have recently used Matplotlib
David Onaiyekan
Last position:
Research Intern at Pattern Recognition Lab
- Spearheaded the integration of a custom Transformer-based encoder into the AFFGANwriting pipeline, replacing the legacy VGG19 architecture to capture richer, high-fidelity writer-style representations.
- Boosted user-study pick-rates by 40%, demonstrating a significant leap in the perceptual quality and realism of the generated handwriting compared to the baseline model.
- Enhanced OCR performance by 20% by implementing a teacher-student framework that leveraged a TrOCR benchmark model for auxiliary training alignment
Muntaha Shams
Last position:
AI Engineer (Freelance) at Upwork
- Delivered 40+ AI projects and 23 strategic consultations for international clients (US, Europe, Middle East), achieving a 98% job success rate and building long-term partnerships.
- Developed and deployed production-grade AI solutions in computer vision, NLP, deep learning, and generative AI (LLMs, RAG pipelines, Stable Diffusion, OCR, chatbots), enabling automation and improving client efficiency by up to 70%.
- Designed and fine-tuned large language models (LLMs), including prompt engineering and integration with enterprise knowledge bases, leading to smarter decision-making and reduced manual effort.
- Built real-time computer vision applications (detection, segmentation, OCR) and integrated them into business systems, significantly enhancing accuracy and scalability.
- Consulted startups and enterprises on AI strategy, architecture, and deployment (cloud & on-premise), accelerating product development and reducing time-to-market.
- Managed complete AI project lifecycles (requirements gathering, solution design, deployment, support) in agile, international, and cross-functional environments, ensuring high-quality delivery.
Puranjan Bandyopadhyaya
Last position:
Internship - Generative AI at Continental
- Gathered tire images and their feature descriptions.
- Cleaned dataset of image metadata using pandas.
- Stored image feature embeddings in Chroma vector db.
- Used image augmentations to increase dataset size.
- Used sklearn to create shuffled datasets and imbalanced-learn to balance class sizes in dataset.
- Used PyTorch to train and test different neural networks.
- Validated model using custom accuracy metric based on similarity search in ChromaDB.
- Visualized accuracy predictions using matplotlib.
- Plugged trained model into DreamBooth to train stable diffusion model and generate new images of tires.
- Created custom Docker image in Amazon Elastic Container Registry for machine learning script.
Pawan Saxena
Last position:
CAPTCHA Recognition using CRNN
- Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
- Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
- Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
- Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
- Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib
Ekaansh Khosla
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Aqsa Younus
Last position:
Multilingual Translation Tool - NLP Project
- Integrated MarianMT (Marian Machine Translation) models to ensure high-quality neural machine translation (NMT).
- Managed model loading and tokenization via Hugging Face Transformers, optimizing for offline caching and reproducibility.
- Planned extensions: language auto-detection, batch translations, and streamlined GPU inference with PyTorch.
Discover over 15,000 top freelancers
Statistics of experts using Matplotlib
Aggregated from the professional profiles of matched freelancers.
Experience
7 years (Germany: 11 years)
Position duration
1.3 years (Germany: 2 years)
Positions per freelancer
5 (Germany: 7)
Top business areas
Information Technology, Research and Development, Product Development
Top industries
Information Technology, Education, Manufacturing
Certification focus areas
Business Intelligence, Information Technology, Research and Development
Bachelor's degree or higher
100%
Master's degree or higher
100% (Germany: 85%)
Certifications per freelancer
3 (Germany: 2)
Most common languages
English, German, Urdu
Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Nuremberg 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 Nuremberg 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it does
Matplotlib is a Python library for creating static, animated, and interactive plots. Companies use it for reports, dashboards, notebooks, research outputs, and product-facing visuals where control over every axis, label, and style matters. It is often the first choice when teams need precise charts rather than template-heavy visuals.
Where it fits
- Exploratory analysis in Jupyter and Python scripts
- Publication figures for science, engineering, and product work
- Embedded plots for internal tools and reporting pipelines
- Custom chart styling that must follow brand or editorial rules
Matplotlib often sits beside NumPy, pandas, and SciPy, and it is commonly used with Seaborn for higher-level statistical plots.
Typical tasks
Strong specialists help teams clean up axes, legends, color maps, annotations, subplots, and export settings. They also build reusable plotting functions so charts stay consistent across notebooks, services, and reports. When needed, they can turn rough data output into figures that are readable in slides, PDFs, and web apps.
Why teams hire
Companies bring in freelance Matplotlib experts when chart quality is slowing down analysis or when internal plots need a more professional finish. This is common in research groups, data teams, manufacturing, finance, and software products with reporting features. In Nuremberg, remote support works well for most charting work, while on-site sessions can help align style and workflow.
Skills that matter
A strong professional understands Python data structures, data cleaning, figure layout, and the limits of different backends. They know when to use Matplotlib directly and when to combine it with pandas plotting, Seaborn, or Plotly for a specific task. Good work is clear, reproducible, and easy for other specialists to extend.
Signs you need help
- Charts are hard to read or inconsistent
- Plot code is duplicated across notebooks or modules
- Exported figures look wrong in PDF or presentation decks
- Team members need help with custom layouts or annotations
If your team already uses mpl or Matplotlib and output quality still lags behind the analysis, a specialist can usually tighten the workflow quickly.
Frequently asked questions
Need clarity? These are the questions we hear most often about Matplotlib.
Matplotlib is used to turn Python data into clear charts, plots, and figures. Teams rely on it for exploratory analysis, reporting, scientific visuals, and product dashboards. It is especially useful when you need fine control over labels, axes, subplots, and export quality.
Matplotlib gives the most direct control over the final figure and is often the base layer for other plotting tools. Seaborn sits on top of it and makes common statistical charts easier to produce, while Plotly is a better fit when you need richer interactivity in the browser. Many teams use Matplotlib for precision and pair it with Seaborn for speed.
A strong Matplotlib specialist should also be comfortable with Python, NumPy, and pandas. Practical skills include data cleaning, layout control, styling, annotation, and exporting to formats like PNG, SVG, or PDF. Experience with Jupyter notebooks and reproducible scripts is also important.
A Matplotlib project usually needs outside help when charts are inconsistent, hard to maintain, or difficult to present. That often happens when teams need custom figure layouts, branded visuals, reusable plotting code, or support for large notebook workflows. A specialist can usually clean up both the code and the output.
Most Matplotlib work can be done remotely because the main deliverables are code, figures, and review feedback. On-site collaboration can help when a team wants to align on plotting standards, report templates, or a shared Python workflow. In Nuremberg, both options are realistic depending on how closely the specialist needs to work with your team.
In Python conversations, Matplotlib is often shortened to mpl. People usually mean the same plotting library when they say either term. If a candidate says they work with mpl, ask for examples of figure design, export formats, and integration with pandas or notebooks.
Look for clean examples, readable chart design, and code that is easy to reuse. A strong Matplotlib professional can explain why a layout choice, color map, or annotation approach helps the reader. Good signs are consistent output, thoughtful defaults, and plots that still work when the data changes.
A Matplotlib specialist may deliver plotting scripts, notebook cells, reusable charting functions, style templates, or figure packages for reports and publications. In some projects, they also document plotting standards so other specialists can keep using the same visual style. The best deliverables make later updates simple.
The average hourly rate of freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects is 36 €, which corresponds to a daily rate of about 291 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects, 100% hold at least a Bachelor's degree and 100% hold at least a Master's degree.
On average, freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects have 7 years of professional experience, with a single engagement typically lasting around 1.3 years.
The most common languages among freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects are English (100%), German (83%), and Urdu (33%).
The most common industries among freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects are Information Technology (100%), Education (67%), and Manufacturing (50%).
The most common business areas among freelancers in Nuremberg, Germany who have used Matplotlib in their recent projects are Information Technology (100%), Research and Development (100%), and Product Development (83%).
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.
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Hamburg 
Munich 
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Philipp Thomaschewski
FRATCH CEO
