Streamlit Experts in Berlin
from over 15,000 CVs with fast, precise AI matchingHire experts who turn Python data work into interactive Streamlit apps, dashboards and internal tools, with strong command of pandas, Plotly, APIs and deployment. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts in Berlin, who have recently used Streamlit
Gilad G.
Last position:
European Strategy Atlas – Independent Analytics & Decision-Support Project at Independent Project
Designed and built an end-to-end interactive decision-support application using public European data across 27 EU countries and multiple strategic dimensions. Developed a structured analytical methodology for comparing countries, identifying patterns and trade-offs, and exploring strategic choices rather than presenting static dashboards. Translated complex multidimensional data into guided interactive exploration and learning workflows for non-specialist users. Built the application end-to-end using Python and Streamlit, with AI-assisted development and Git-based version control. Developed the project independently from problem framing and data analysis through methodology, UX logic, implementation and deployment.
Tools: Python, Streamlit, Git, AI-assisted development
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Nikolai G.
Last position:
Clinical Data Manager at Dr. Falk Pharma
- Used OpenCode and AI-assisted software engineering to design, implement, refactor, test, and document an end-to-end RAW/SDTM/ADaM pipeline in R for Dr. Falk Pharma (07/2026), including metadata-driven transformations, automated validation rules and QC, traceability, and reproducible clinical outputs.
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
Jeet P.
Last position:
Global SAP Program Manager at Aldi Sued
- Pioneered first enterprise AI-SAP integration at ALDI SÃœD, deploying AI-driven automation within one of retail's largest SAP S/4HANA programs, eliminating 50% of manual pre-cycle validation time and establishing replicable automation framework across 11 countries
- Led end-to-end SAP project lifecycle management for implementations across SAP S/4HANA and Manhattan Systems, supporting 7,300+ ALDI SÃœD locations globally across Europe and Australia
- Served as primary executive liaison to C-level stakeholders across 11 countries for strategic SAP transformation programs
- Orchestrated automation, performance, and volume testing for critical releases, maintaining 99.9% system SLA compliance during peak retail periods
- Managed cross-functional international teams of 15+ specialists, delivering projects 20% faster than industry benchmarks
- Standardized SAP processes across 11 countries as part of one of retail's largest SAP implementations
- Directly managed €2M budget with 98% allocation accuracy across 12 concurrent projects
- Reduced SAP S/4HANA migration costs by 18% through strategic vendor contract renegotiations and optimization
Ashwin P.
Last position:
Data Scientist at Mercor Intelligence
- Elevated LLM output reliability by engineering domain-specific prompts and evaluation logic, improving reasoning consistency across production language model workflows.
- Designed advanced coding benchmarks and validated solutions to strengthen training and evaluation datasets, improving model performance on technical problem-solving tasks.
- Designed and implemented automated evaluation frameworks for technical reasoning tasks; optimized LLM output reliability by 15% through rigorous prompt engineering and rubric-based benchmarking.
Carlos M.
Last position:
Toxicology & Risk Assessment Consultant at European Food Safety Authority
- Conduct scientific evaluations and risk assessments for substances and materials with relevance to human health, including nanoparticle safety.
Sanu M.
Last position:
Decision Scientist III at Vinted GmbH
Built an FRT (Full Resolution Time) data product in dbt and BigQuery with a MECE ticket lifecycle methodology derived from a unified semantic mapping and ordered event stream.
Delivered reusable macros, modular models, automated unit tests, and a LookML metric layer adopted by Process Improvements and Ops.
Overhauled FRT experiments using quasi-experimental and pre-post causal analyses to demonstrate that slower resolution affected GMV, enabling shifting from a blanket 70%-in-48h SLA to problem-specific targets and providing the analytical foundation for SLA redesign.
Robin S.
Last position:
Consultant, Data Science & Engineering at valantic Digital Finance GmbH
- Bridged business and engineering for enterprise finance clients, designing data products and cloud pipelines in Python, SQL Server, SAP Datasphere, and Tagetik
- Conceived, built, and containerised a Python/FastAPI universal connector that syncs SAP S/4HANA and other SQL/NoSQL sources to Tagetik, deployed on Google Cloud Run and Microsoft Azure, cutting a critical 90-minute data load to approximately 80 seconds (65× faster)
- Architected a medallion-layer SQL Server warehouse ingesting approximately 500 GB/day from 11 ERP instances, automating daily refreshes (full load under 6 minutes) and freeing 20–30 finance staff from days of manual data consolidation
- Led cross-functional workshops to design enterprise EPM target architecture for a leading Southeast-Asian telecom (CAPEX, OPEX, revenue), translating requirements into data-model specifications and integration blueprints now being built by the client’s implementation team
- Delivered selected projects including a consolidated data & reporting warehouse for a global manufacturer (10 k+ employees), NFI reporting for an international management & technology consultancy, and CAPEX/OPEX planning for a Southeast-Asian telecom (20 k+ employees)
Mohamed Y.
Last position:
AI Engineer at AlphaFMC
- Architect AI systems across build-vs-buy layers; guide clients on technology selection, evaluation, integration patterns, and governance to reduce risk and time-to-value.
- Implement Azure/Snowflake solutions (RAG pipelines, chatbots, data agents) including ingestion, retrieval, orchestration, and monitoring.
- Partner with stakeholders to translate business needs into deployable AI roadmaps and reference architectures; align with existing data platforms and security controls.
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.
Ivan K.
Last position:
Product Analyst at Sentryc GmbH
- Led data analytics projects, including data mining, exploratory research, A/B testing, KPI definition, and result interpretation
- Had a key role in scope and requirements definition of new features, creation of user flows, proof of concepts creation, and client personas establishment
- Initiated a data project related to clustering counterfeit listings based on language similarities, which was projected to reduce internal costs by 20%
- Led data migration project from Zoho Analytics to Power BI as well as from Google Analytics to Piwik
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.
Katharina S.
Last position:
AI Engineer
- Designed and implemented end-to-end automated workflows for extracting structured data from semi-structured PDF documents including invoices and medical reports
- Leveraged Optical Character Recognition (OCR) technology and large language models to parse documents and generate validated JSON schemas
- Engineered prompt optimization strategies and rule-based classification hierarchies to enhance parsing accuracy across diverse document layouts
- Established quality assurance framework using evaluation metrics to validate output against ground truth datasets with 96% accuracy
Discover over 15,000 top freelancers
Statistics of experts using Streamlit
Aggregated from the professional profiles of matched freelancers.
Experience
11 years
Position duration
1.7 years (Germany: 1.8 years)
Positions per freelancer
7 (Germany: 9)
Top business areas
Product Development, Business Intelligence, Information Technology
Top industries
Information Technology, Healthcare, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100% (Germany: 99%)
Master's degree or higher
62% (Germany: 75%)
Doctorate
31% (Germany: 18%)
Certifications per freelancer
1 (Germany: 2)
Most common languages
German, English, French
Speak two or more languages
100%
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 Streamlit
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.
Streamlit 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%)
- Healthcare (54%)
- Professional Services (54%)
- Banking and Finance (38%)
- Education (31%)
- Food and Beverage (23%)
- Manufacturing (23%)
- Retail (23%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Streamlit does
Streamlit is an open-source Python framework for turning data scripts and machine learning models into interactive web applications. It lets teams create user interfaces with Python instead of building a separate frontend. Typical results include analytical dashboards, model demos, data explorers and internal decision tools.
Core application work
Streamlit specialists build applications that connect data, logic and user input in one clear workflow. They use widgets, session state, caching and layouts to make technical results accessible to business users. Strong work includes clear error handling, responsive interactions and a structure that can grow beyond a proof of concept.
Ecosystem and tooling
Streamlit projects often rely on a broader Python data ecosystem and a well-defined delivery process.
- Connect pandas, NumPy and SQL data sources
- Present charts with Plotly, Altair or native components
- Integrate machine learning models and API services
- Manage secrets, environments and reproducible dependencies
- Deploy through Streamlit Community Cloud or private infrastructure
When companies need specialists
Freelance expertise helps when a data team has a working notebook but needs a usable application. It is also valuable when an existing Streamlit app needs better performance, access control, testing or deployment. In Berlin, specialists may support local product, research and industrial teams on-site, remotely or in a hybrid setup.
Delivery and adjacent skills
The best fit depends on the system around the app. Useful adjacent capabilities include Python packaging, Git workflows, SQL, cloud services, containerisation, authentication and observability. For production-facing work, professionals should understand data privacy, dependency management, automated testing and how to separate presentation logic from business logic.
What strong professionals bring
Strong Streamlit professionals explain technical results in terms users can act on. They ask how data is refreshed, who can access each view and what happens when a source fails. Look for a clear portfolio, thoughtful interface choices and evidence of reliable deployment rather than a collection of attractive charts alone. Berlin collaboration can work in English, with German useful where stakeholders and documentation require it.
Frequently asked questions
Before you brief your next project: the most common questions about Streamlit.
Streamlit is commonly used for interactive data applications, dashboards, model demonstrations and internal tools. It is especially useful when a Python-based team needs to share analysis or predictions without maintaining a separate frontend stack.
Streamlit usually offers a faster path from Python analysis to a usable interface than a custom web application. Dash can provide more granular control over callback-driven dashboards, while a custom frontend is often preferable when the product needs complex navigation, extensive branding or highly specialised interactions.
A strong Streamlit specialist should understand Python, pandas, SQL and data visualisation tools such as Plotly or Altair. Experience with APIs, authentication, cloud deployment, Docker, testing and machine learning workflows is also valuable when the application must move beyond a prototype.
A small Streamlit dashboard may need focused experience with data preparation, widgets and deployment. A production application calls for deeper knowledge of performance, session state, secrets, access control, testing and operational monitoring, so the required expertise depends on reliability and user expectations.
Yes. Streamlit work is well suited to remote collaboration because code, data contracts and deployments can be reviewed online. Berlin-based teams should agree on working hours, documentation practices and whether English or German is needed for stakeholder communication.
Streamlit can support production use when its application model matches the requirements and the surrounding infrastructure is designed carefully. Professionals should address caching, resource use, authentication, secrets, deployment, logging and failure handling instead of treating a prototype as production-ready.
Review whether the Streamlit application is understandable, responsive and reliable with realistic data. Ask how the professional handles state, invalid input, slow queries, dependency updates, access permissions and deployment, then inspect the code structure and documentation.
Many professionals value Streamlit because it connects Python data work with visible user outcomes without requiring a separate frontend implementation. Projects can range from rapid exploratory tools to polished internal applications, provided the scope, data access and deployment expectations are defined clearly.
The average hourly rate of freelancers in Berlin, Germany who have used Streamlit in their recent projects is 82 €, which corresponds to a daily rate of about 655 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Streamlit in their recent projects, 100% hold at least a Bachelor's degree, 62% hold at least a Master's degree, and 31% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Streamlit in their recent projects have 11 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Berlin, Germany who have used Streamlit in their recent projects are German (100%), English (100%), and French (23%).
The most common industries among freelancers in Berlin, Germany who have used Streamlit in their recent projects are Information Technology (69%), Healthcare (54%), and Professional Services (54%).
The most common business areas among freelancers in Berlin, Germany who have used Streamlit in their recent projects are Product Development (92%), Business Intelligence (85%), and Information Technology (85%).
Main locations of FRATCH Experts, who have recently used Streamlit
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 Request a free demo
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Philipp Thomaschewski
FRATCH CEO
