Seaborn Expert in Berlin
for clear statistical visuals, matched in minutes with vetted and available professionalsHire experts who create publication-ready statistical charts, analytical dashboards and data stories with Seaborn, Matplotlib and pandas. FRATCH precisely matches you with vetted, available freelancers who fit your project and can start quickly.
Meet FRATCH Experts in Berlin, who have recently used Seaborn
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
Ibrahim H.
Last position:
Senior Full Stack / AI Engineer at Punktum Digital GmbH
- Context: Healthcare and laboratory teams required faster document analysis, treatment-planning support, and reliable AI workflows for MR/VR-assisted operations.
- Contribution: Built the AI healthcare platform, model/agent workflows, VR-glasses deployment platform, REST APIs, Next.js/React interfaces, and CI/CD pipelines.
- Impact: Delivered a production-ready AI product foundation that improved clinical document review, supported laboratory automation, and made VR fleet deployment manageable across environments.
Tech: TypeScript, Next.js, Node.js, React, Java, Spring Boot, Python, PyTorch, TensorFlow, Docker, PostgreSQL, OpenAPI, GitLab, GitHub Actions.
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.
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.
Joseph Chris Adrian R.
Last position:
Data Scientist II at Amazon
- Engaged stakeholders to understand requirements and define the project scope and success criteria
- Demonstrated adaptability by quickly ramping up in a complex, ambiguous regulatory space
- Authored comprehensive science design, architecture review and final methodology documentation ensuring reproducibility
- Gathered data stored in Amazon Redshift and Amazon S3 using SQL
- Performed exploratory data analysis and feature engineering using Python (matplotlib and seaborn), PySpark and Amazon EMR
- Developed and validated machine learning models to facilitate optimization, time-series forecasting, anomaly detection and classification
- Developed machine learning models using Python libraries such as scikit-learn, numpy and pandas
- Deployed the machine learning model using AWS cloud platform (MLOps), especially AWS SageMaker
Manasa N.
Last position:
Fundraiser at Talk2Move
- Represented NGOs
- Engaged in persuasive communication and public outreach
- Enhanced collaboration, communication, and decision-making skills
Discover over 15,000 top freelancers
Statistics of experts using Seaborn
Aggregated from the professional profiles of matched freelancers.
Experience
10 years
Position duration
2.1 years (Germany: 1.8 years)
Positions per freelancer
6 (Germany: 7)
Top business areas
Business Intelligence, Information Technology, Product Development
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
85% (Germany: 82%)
Doctorate
15% (Germany: 20%)
Certifications per freelancer
1 (Germany: 2)
Most common languages
German, English, Hindi
Speak two or more languages
93% (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 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 Seaborn
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.
Seaborn 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 (79%)
- Education (57%)
- Healthcare (43%)
- Professional Services (36%)
- Retail (36%)
- Transportation (21%)
- Manufacturing (21%)
- Government and Administration (21%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Statistical visualization
Seaborn is a Python library for creating informative statistical graphics from structured data. It builds on Matplotlib and works naturally with pandas DataFrames, making relationships, distributions and category comparisons easier to explore. Its themes, color palettes and high-level functions support clear visuals without requiring every chart element to be configured manually.
Typical outputs
Seaborn specialists turn analytical questions into visuals that teams can interpret and reuse:
- Distribution plots that reveal spread, skew and unusual observations
- Relationship charts for correlations, trends and grouped comparisons
- Categorical plots for rankings, counts and segment analysis
- Facet grids that compare patterns across several dimensions
- Presentation-ready figures exported for reports and applications
Python ecosystem
Effective Seaborn work depends on more than chart syntax. Professionals commonly combine it with Python, pandas for data preparation, NumPy for numerical operations and Matplotlib for detailed styling or custom annotations. Jupyter notebooks support exploration, while tools such as Plotly, Altair or dashboard frameworks may be appropriate when interaction is required.
When expertise helps
Companies often bring in freelance Seaborn expertise when raw analysis needs a consistent visual language or an existing notebook has become difficult to maintain. This is useful for product analytics, scientific reporting, finance, marketing research and machine learning workflows. In Berlin, specialists may contribute remotely or work with local teams on shared notebooks, review sessions and documentation.
Project signals
Specialist support is valuable when charts communicate different results depending on filters, categories or data transformations. It also helps when visuals look attractive but do not explain uncertainty, sample structure or scale accurately:
- A reporting workflow needs repeatable chart generation
- Analysts need reusable functions and consistent themes
- A notebook must become a documented deliverable
- Figures need review for misleading scales or comparisons
- Visual outputs must support a wider data product
Strong Seaborn practice
Strong professionals begin with the analytical question, inspect the data model and select a chart that fits the evidence. They handle missing values, categorical ordering, legends, color accessibility and annotations deliberately. They also separate data preparation from presentation logic, keep plots reproducible and explain when Seaborn should give way to Matplotlib customization or an interactive visualization tool.
Frequently asked questions
Quick answers to the questions that come up most around Seaborn.
Seaborn is used to create statistical data visualizations in Python. It is well suited to distributions, correlations, categorical comparisons, regression views and multi-variable exploration, especially when data is stored in pandas DataFrames.
Seaborn provides a higher-level interface and useful statistical defaults, so common analytical charts can be produced with less setup. Matplotlib offers finer control over individual figure elements, and strong professionals often use both rather than treating them as competing tools.
A strong Seaborn specialist should also understand Python, pandas, NumPy and Matplotlib. Familiarity with Jupyter, data cleaning, statistical reasoning and dashboard tools helps when charts need to move from exploration into a wider reporting workflow.
Describe the data sources, analytical questions, intended audience and required outputs. For Seaborn work, it also helps to share sample data, existing notebooks, preferred export formats and any accessibility or brand requirements.
The right level depends on the work rather than a fixed duration. A focused charting task may need someone comfortable with pandas and visual design, while a reusable reporting system calls for deeper Python structure, statistical judgment and testing.
Yes. Seaborn projects usually rely on notebooks, version control, shared datasets and clear review notes, which support remote collaboration. On-site sessions can still help when stakeholders need to agree on analytical definitions or visual standards.
Review whether the chart answers a defined question, represents the data honestly and remains readable across relevant categories. Ask to see reproducible code, clear data transformations, sensible scales, accessible colors and explanations of choices made in Seaborn.
Seaborn may be a poor fit when users need rich browser interaction, live streaming views or highly customized graphics without a Python execution environment. In those cases, a specialist may recommend Plotly, Altair, a dashboard framework or a dedicated JavaScript visualization library.
The average hourly rate of freelancers in Berlin, Germany who have used Seaborn in their recent projects is 71 €, which corresponds to a daily rate of about 570 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Seaborn in their recent projects, 100% hold at least a Bachelor's degree, 85% hold at least a Master's degree, and 15% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Seaborn in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 2.1 years.
The most common languages among freelancers in Berlin, Germany who have used Seaborn in their recent projects are German (100%), English (93%), and Hindi (21%).
The most common industries among freelancers in Berlin, Germany who have used Seaborn in their recent projects are Information Technology (79%), Education (57%), and Healthcare (43%).
The most common business areas among freelancers in Berlin, Germany who have used Seaborn in their recent projects are Business Intelligence (86%), Information Technology (86%), and Product Development (64%).
Main locations of FRATCH Experts, who have recently used Seaborn
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
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
