Seaborn Experts in Berlin
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Meet FRATCH Experts in Berlin, who have recently used Seaborn
Wolfram Knan
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 Hilali
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 Rao
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.
Deependra Pokhrel
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.
Phil Howson
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
Sebastian Papazoglou
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 Großer
Last position:
Machine Learning Engineer at docmetric GmbH
- Analyzed patient data for various clients
- Developed complex analysis pipelines
- Performed quality assurance on methods
Srikar Kodi
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 Khan
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 Thota
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 Fleischer
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 Rampalli
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 Regis
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 Naik
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 (Germany: 11 years)
Position duration
2.1 years (Germany: 1.9 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 30 Aug 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What Seaborn is
Seaborn is a Python library for statistical data visualization. It sits on top of Matplotlib and works closely with pandas, so specialists can turn tables and data frames into clear plots with less code.
What it is used for
- Exploratory analysis and quick pattern finding
- Heatmaps, distribution plots, and categorical charts
- Correlation views, pair plots, and regression visuals
- Presentation-ready charts for reports and notebooks
Common project work
Companies bring in Seaborn professionals when data needs to be easier to read and explain. That often includes notebook analysis, dashboard support, model evaluation visuals, and chart cleanup for internal reviews or client-facing work.
Skills around it
Strong specialists know more than the library itself. They usually work with pandas, Matplotlib, NumPy, Jupyter, and Python data pipelines, and they understand how to choose the right chart for the question, not just make a chart look nice.
When to hire freelance help
- Your team needs clean visual analysis fast
- Existing plots are hard to read or inconsistent
- A project uses pandas data and Python notebooks
- You need support for a report, prototype, or handover
In Berlin, Seaborn expertise is often useful for analytics teams, product data work, and consulting projects that move between office and remote collaboration.
What strong experts deliver
A good Seaborn specialist writes clear, maintainable plotting code and knows how to adjust color, layout, and annotations for real audiences. They also document the visuals well, so others can reuse the work in Python, notebooks, and reporting flows.
Frequently asked questions
Quick answers to the questions that come up most around Seaborn.
A strong Seaborn specialist uses it to create statistical charts that make data easier to compare and explain. It is common for exploratory analysis, notebook reporting, and visual summaries that sit on top of pandas data. Teams use it when they need fast, readable plots in Python without building every chart from scratch.
Seaborn is usually the faster choice for statistical plots and cleaner defaults, while Matplotlib gives deeper control over every visual detail. Many specialists use both together: Seaborn for the first version and Matplotlib for fine-tuning. If your team already works in Python, that combination is often the practical path.
Seaborn is the main search term, but many people shorten it to sns in code and project notes. In practice, you should also look for Python, pandas, and Matplotlib skills, because those tools usually come with it. That mix matters more than the label alone.
A strong Seaborn freelancer can clean up exploratory notebooks, build charts for analysis reviews, and create reusable visuals for reporting. They are also useful when a team needs help choosing the right plot type for distributions, categories, or relationships. The best experts make the output easy for others to read and reuse.
Most Seaborn work does not need a huge team, but it does need someone who understands both the library and the data behind it. Simple chart requests may be enough for a focused specialist, while broader analytics work needs someone who can handle pandas, notebook flow, and chart design together. The key is not years, but practical output quality.
Yes, Seaborn work is often remote because the core deliverables are notebooks, charts, and reusable Python code. In Berlin, that fits well with teams that move between local workshops and remote delivery. On-site sessions can help at the start, but most hands-on work can continue online.
A good Seaborn specialist usually knows pandas for data shaping, Matplotlib for visual control, and Jupyter for analysis work. Python is essential, and NumPy often appears in data prep. If the person also understands data storytelling, the charts are usually much more useful.
Look for clear chart choices, clean code, and sensible use of labels, color, and layout in Seaborn work. Strong experts can explain why a plot fits the question and can adjust the visual for different audiences. If they also write reusable functions or notebook notes, that is a good sign.
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
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Philipp Thomaschewski
FRATCH CEO
