Plotly Experts in Germany
with precise AI matching, vetted freelancers and fast access to proven data visualisation skillsHire experts who create interactive charts, analytical dashboards and visual data products with Plotly, Plotly Express and Dash. FRATCH matches your requirements precisely with vetted, available freelancers in minutes.
Meet FRATCH Experts in Germany, who have recently used Plotly
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.
Manoj K.
Last position:
Data Analyst Work Student at Biebelhausener Mühle seit 1647 GmbH
- Managed and maintained daily sales and transaction data, ensuring data accuracy and integrity for operational reporting and analysis.
- Analyzed customer purchasing patterns to support inventory planning and improve product availability.
Rutger B.
Last position:
Partner & Managing Director at AI.IMPACT
- Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
- End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
- Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
- Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
- Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
- Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
- Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles
Nomaira F.
Last position:
Freelance Product Designer / Design Engineer at Independent
- Design and build client web apps and self-directed products end-to-end, covering product design, design systems, and full-stack front-end on React, TypeScript, Tailwind, and Supabase.
- Designed and shipped a compliance and staff-records web application for a UK transport operator, covering data modelling, UX, and front-end build on Supabase with row-level security and Edge Functions.
- Built Merita, a private-by-default achievement-tracking and performance-review app, in a 48-hour hackathon (SheBuilds). It covers win logging linked to goals and competency frameworks, AI-assembled review packets with token-gated sharing, and a Promotion Readiness view, and is built on React, TypeScript, Tailwind, shadcn/ui and Supabase with row-level security and Edge Functions.
- Designed and built Pantressa, a grocery-tracking, meal-planning and budgeting app, owning product design through front-end delivery on React, TypeScript, Tailwind and Supabase.
Deepak R.
Last position:
Machine Learning Engineer at go AVA GmbH
- Designed and built a multi-tenant Python/Flask API platform with JWT + API-key authentication, scoped access control, and service-level orchestration as the backbone for AI applications.
- Built a multimodal RAG system with hybrid chunking, dense/sparse embeddings, hybrid retrieval, reranking, and vector search to deliver grounded, high-precision responses across enterprise data.
- Productionized AI workflows with Docker, CI/CD, Redis-backed async job tracking, webhook callbacks, external AI/media service integrations, and runtime health/reliability controls.
Stephan B.
Last position:
Freelance Data Scientist at Baier Data & AI Consulting
Mugisha E.
Last position:
Freelancer Business Data Analyst at Study Boundless
- Manage WordPress websites, ensuring SEO-friendly structures and high-performance functionality
- Create and optimize Google Ads campaigns, leveraging data to enhance conversion rates and ROI
- Develop Looker Studio & Power BI dashboards to track customer behavior, sales trends, and digital performance
- Implement Google Tag Manager (GTM) and Google Analytics (GA4) to enable precise event tracking and reporting
Christian S.
Last position:
Data-Scientist/AI Engineer at The Marcom Engine GmbH & Co. KG
- Concept creation and implementing AI Agents in AWS Cloud
- Continuously alignment with stakeholders
- Collaborate with DevOps
- Technologies: Git, CI/CD (GitHub Actions), Python/ML, Streamlit, Deno/typescript, AWS SAM, AWS Bedrock, AWS Lambda, AWS Dynamo DB, AWS S3, AWS Event Bridge etc.
Yenal Y.
Last position:
Shiny R Development at RadixITS Gbr
- Implementation and mapping of regulatory requirements (CSRD, ESRS) in Shiny dashboards and backend functions
- Design and development of data-driven modules in Shiny incl. ESG metrics and reporting templates
- Integration of data sources (SQL, SAP HANA, APIs, CSV/Excel) via DBI, odbc, httr and readr
- Creation of interactive visualizations with plotly, highcharter and DT (DataTables)
Sebastian D.
Last position:
Data Scientist at CLADE GmbH
- Designed and implemented a robust Python-based data processing framework that supported the transition from R to Python and significantly improved data science productivity by providing maintainable, standardized modules for frequently used workflows, following coding best practices and DevOps principles
- Evaluated, trained, and deployed machine learning models on cloud platforms and edge devices, enabling fully automated mid-infrared (MIR) data evaluation pipelines that eliminated manual analysis steps and significantly shortened the time from measurement to prediction for customers and internal stakeholders
- Analyzed and interpreted multivariate MIR spectral data from the company’s proprietary analyzer using R and Python, supporting reliable identification and quantitation of chemical compounds in solution
Julian H.
Last position:
Working Student / Master's Thesis Student Software Development at Scale GmbH
- Tech-Stack: Python, Qt, tensorflow.js, plotly, Angular, TypeScript, HTML, CSS, Git
Stephan S.
Last position:
Senior Data/ML Consultant & Technical Lead at Jolin.io
Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)
Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)
Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)
Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)
Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)
Prakriti J.
Last position:
Student Research Assistant at Heidelberg University
- Built a Databricks ETL pipeline to ingest and clean JSON book metadata from the OpenLibrary API.
- Transformed nested datasets using Python/PySpark and structured them into curated analytical tables.
- Loaded processed datasets into Snowflake to enable SQL based reporting and metadata analysis.
Stefan L.
Last position:
Dashboard for Interactive Data Analysis at LennardtundBirner GmbH
Development & deployment of an interactive dashboard that allows users to select datasets for visual analysis.
The application supports filters, AI-based interpretations, and a chatbot for user interactions.
shiny, openai, mirai, plotly, mapgl, duckdb, AWS, ShinyProxy, Docker Swarm
Prasanna H.
Last position:
Master's Thesis Student at Robotics Research Lab, TU Kaiserslautern
- Benchmarked datasets, collected real-world off-road data (~9000 images) and generated simulation datasets using Unreal Engine.
- Developed Gen-AI image segmentation in Unreal Engine, reducing time from 1-2 days to 5-10 minutes.
- Built Generative AI data enhancement pipeline. Achieved an improvement in synthetic data by +49% mIoU.
- Tech: Python, PyTorch, C++, Git, LangChain, Gen-AI, Linux, W&B, OpenCV, Labelme.
Discover over 15,000 top freelancers
Statistics of experts using Plotly
Aggregated from the professional profiles of matched freelancers.
Experience
11 years
Position duration
2.1 years
Positions per freelancer
7
Top business areas
Information Technology, Business Intelligence, Research and Development
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100%
Master's degree or higher
89%
Doctorate
19%
Certifications per freelancer
2
Most common languages
German, English, French
Speak two or more languages
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 Germany 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 Germany using Plotly
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.
Plotly 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 (69%)
- Education (51%)
- Healthcare (33%)
- Manufacturing (33%)
- Professional Services (33%)
- Banking and Finance (31%)
- Automotive (22%)
- Insurance (18%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Interactive visualisation
Plotly is a graphing library for creating interactive, browser-based data visualisations. It supports Python, R, and JavaScript, with Plotly.py used widely for analytical applications and reporting. Teams use it to turn structured data into charts that users can explore, filter and understand.
Charts and applications
Plotly covers statistical, scientific and business visualisation needs, from time-series and scatter plots to maps, 3D views and financial charts. With Dash, teams can connect charts, controls and data processing in a complete analytical web application. Outputs can support internal decision-making, customer portals and operational monitoring.
- Interactive business intelligence dashboards
- Scientific and engineering data exploration
- Financial, geospatial and time-series reporting
- Embedded charts for web applications
Ecosystem and tooling
Strong Plotly specialists work across Plotly.py, Plotly Express and the lower-level graph objects API. They often combine the library with pandas, NumPy, Jupyter, SQL and cloud data services. Dash adds callbacks, layouts, reusable components and deployment patterns for production-facing applications.
When expertise helps
Companies bring in freelance Plotly expertise when static reports no longer answer changing business questions or when an analytics prototype must become a dependable product. Specialists can shape the visual model, connect live data sources, improve responsiveness and establish patterns that internal teams can maintain. In Germany, this can support both remote delivery and on-site collaboration across data-heavy industries.
- Replace manual spreadsheet reporting
- Turn notebooks into usable applications
- Connect dashboards to governed data
- Improve chart clarity and interaction design
What strong specialists deliver
A capable professional starts with the decisions a visualisation must support, not with a chart type. They choose suitable encodings, preserve accurate scales, handle missing data and make interactions predictable. They also separate data preparation from presentation logic, structure Dash callbacks carefully and consider accessibility, performance and secure handling of business data.
Selecting the right professional
Review work that resembles your data, audience and delivery environment rather than judging screenshots alone. Ask how the specialist tests transformations, manages refreshes, handles large datasets and documents the application. Relevant experience with Python, SQL, pandas, deployment and German or English collaboration can matter as much as visual polish when the project involves several stakeholders.
Frequently asked questions
Curious about Plotly? Here are the answers that come up again and again.
Plotly is used to create interactive charts, maps, statistical graphics and analytical dashboards. Teams can publish visualisations in notebooks, web pages or Dash applications, allowing users to inspect data rather than only view a static image.
Plotly focuses on interactive, web-ready visualisations and works well when users need hover details, filtering or linked views. Matplotlib offers broad control for static scientific plots, while Tableau provides a more packaged business intelligence environment; the right choice depends on deployment, governance and the team’s coding skills.
A strong Plotly specialist usually understands Python, pandas, SQL and data modelling. For application work, experience with Dash, web layouts, callbacks, APIs, authentication and cloud deployment is valuable, while domain knowledge helps turn business questions into useful visual views.
The required Plotly experience depends on the deliverable. A focused chart or notebook may need visualisation and data-wrangling skills, while a production Dash application calls for stronger knowledge of application structure, testing, performance, deployment and ongoing maintenance.
Plotly projects are often well suited to remote collaboration because requirements, data samples and dashboard reviews can be shared digitally. For teams in Germany, agree early on working language, meeting times, data access and whether occasional on-site workshops are needed.
Ask a Plotly professional to explain why specific chart forms, scales and interactions were chosen. Review how they validate data, handle edge cases, document the code and test performance; a polished dashboard is not enough if its visual logic can mislead users.
Plotly.py is the Python library that includes both the concise Plotly Express interface and the more detailed graph objects API. Plotly Express helps specialists create common charts quickly, while graph objects provide finer control over traces, layout, annotations and complex interactions.
Dash is useful when Plotly charts need to become part of an interactive Python web application. It adds layouts, controls and callbacks so users can change inputs and receive updated results, making it suitable for analytical tools that go beyond a collection of standalone charts.
The average hourly rate of freelancers in Germany who have used Plotly in their recent projects is 93 €, which corresponds to a daily rate of about 746 € based on an 8-hour working day.
Of the freelancers in Germany who have used Plotly in their recent projects, 100% hold at least a Bachelor's degree, 89% hold at least a Master's degree, and 19% hold a doctorate.
On average, freelancers in Germany who have used Plotly in their recent projects have 11 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers in Germany who have used Plotly in their recent projects are German (100%), English (98%), and French (22%).
The most common industries among freelancers in Germany who have used Plotly in their recent projects are Information Technology (69%), Education (51%), and Healthcare (33%).
The most common business areas among freelancers in Germany who have used Plotly in their recent projects are Information Technology (90%), Business Intelligence (80%), and Research and Development (78%).
Main locations of FRATCH Experts, who have recently used Plotly
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 Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
Munich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
