Streamlit Experts in Berlin
in minutes from over 15,000 CVs with the power of AIHire experts who turn Python scripts into Streamlit apps, interactive dashboards, data apps, and internal tools. They work with widgets, state, deployment, and data pipelines, with fast, precise matching to vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Streamlit
Gilad Gotesman
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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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
Jeet Pattanaik
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 Parthasarathy
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 Montefusco Pereira
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 Mishra
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 Steinkühler
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 Yousfi
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 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.
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.
Katharina Schachmatov
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
Ivan Kostov
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
Discover over 15,000 top freelancers
Statistics of experts using Streamlit
Aggregated from the professional profiles of matched freelancers.
Experience
10 years (Germany: 11 years)
Position duration
1.7 years (Germany: 1.8 years)
Positions per freelancer
6 (Germany: 8)
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: 98%)
Master's degree or higher
58% (Germany: 75%)
Doctorate
25% (Germany: 17%)
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 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 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What Streamlit does
Streamlit is a Python framework for building data apps with a small amount of code. It is used for dashboards, model demos, internal tools, and fast prototypes that need to be shared with teams or clients. Many companies bring in Streamlit specialists when a notebook has to become a usable app.
Where it fits
Streamlit works well when speed matters and the app is centered on data, not complex front-end logic. It is often chosen over heavier web stacks for analytics workflows, proof of concepts, and decision tools. In Berlin, it is a common fit for product, research, and data teams that need clear collaboration.
Typical work
- Build dashboards for KPIs, exploration, and reporting
- Wrap machine learning models in a simple interface
- Create internal tools for review, filtering, and input
- Connect apps to APIs, SQL databases, and file sources
- Package and deploy apps for team use
Ecosystem and tooling
Strong Streamlit professionals know Python well and usually work with pandas, NumPy, plotly, Altair, scikit-learn, SQL, and cloud deployment tools. They understand app state, caching, forms, authentication patterns, and how to keep the codebase readable as the app grows. They also know when Streamlit is enough and when another stack is a better choice.
When freelancers help
Companies often need outside expertise when a prototype must be hardened, an existing app is slow or fragile, or a data team needs delivery support. Freelancers are also useful when the internal team can build the logic but needs help with layout, deployment, or maintainability. For Berlin teams, remote work is common, but on-site collaboration can help with workshop-heavy projects.
What strong specialists deliver
A strong Streamlit specialist ships more than screens. They structure the app, reduce reruns, manage state carefully, handle inputs and outputs cleanly, and make the experience usable for real business work. Good delivery also includes practical documentation, handover, and support for future changes.
Frequently asked questions
Before you brief your next project: the most common questions about Streamlit.
Streamlit is used to turn Python-based data work into interactive apps. Companies use it for dashboards, internal review tools, model demos, and quick decision support. It is especially useful when the goal is to share analysis without building a full custom web application.
Streamlit is usually faster to build with than Dash or Flask for data-focused apps. Dash gives more control for complex interfaces, while Flask is a general web framework that needs more custom front-end work. Streamlit is a strong choice when the app is mostly Python, data, and interaction rather than a large product UI.
A strong Streamlit freelancer should know Python, data handling, and how to work with pandas or SQL. Useful adjacent skills include plotly, Altair, scikit-learn, APIs, and deployment basics. Good specialists also understand app state, caching, and how to keep the code easy to extend.
A small Streamlit prototype can be handled by a specialist who is strong in Python and data apps. More demanding work needs someone who can design clean workflows, improve performance, and prepare the app for team use. The right level depends on whether you need a demo, an internal tool, or a production-facing application.
Yes, Streamlit can support production use when the scope fits its strengths. It works well for internal tools, analytics apps, and model interfaces, especially when authentication, deployment, and state handling are planned carefully. For very large or highly custom product interfaces, another stack may be better.
Both can work well for Streamlit projects. Remote collaboration is common because the code, data, and reviews can be handled online, but on-site time in Berlin can help when teams need workshops, stakeholder sessions, or fast feedback on interfaces. The best choice depends on how much alignment the project needs.
Look for a Streamlit specialist who shows real apps, not only notebooks or short snippets. Good signs are clear structure, sensible state handling, thoughtful UI choices, and stable deployment practices. They should also explain trade-offs clearly and know when to simplify the scope.
No, Streamlit is not the same as a full custom web stack. It is built for fast Python-based apps around data, not for every kind of front-end or product experience. That is why many companies use it for internal tools, prototypes, and analytics workflows, then move elsewhere only if the scope grows beyond it.
The average hourly rate of freelancers in Berlin, Germany who have used Streamlit in their recent projects is 81 €, which corresponds to a daily rate of about 646 € 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, 58% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Streamlit in their recent projects have 10 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 (25%).
The most common industries among freelancers in Berlin, Germany who have used Streamlit in their recent projects are Information Technology (67%), Healthcare (50%), and Professional Services (50%).
The most common business areas among freelancers in Berlin, Germany who have used Streamlit in their recent projects are Product Development (92%), Business Intelligence (83%), and Information Technology (83%).
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
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
