Jupyter Experts in Berlin
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Meet FRATCH Experts in Berlin, who have recently used Jupyter
Dmitry Pankov
Last position:
Freelance Digital Marketing Analyst at Freelance
- Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
- Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
- Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
- Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.
Oleg Abrazhaev
Last position:
Staff Software Engineer at Kpler Germany GmbH
- Delivered a new notifications platform implementation built from scratch to replace existing and upcoming services
- Collaborating with other teams to integrate more domains
Tech stack:
- Data: Scala 3, Apache Kafka, Python, Airflow, Astronomer
- BE-FE: TypeScript, NestJS, Java, Spring Boot, Vue
- Dev-ops: AWS, PostgreSQL, Docker, GitHub Actions, Kubernetes, Helm, ArgoCD
William Nguyen
Last position:
Senior Business Analyst/Requirements Engineer at Finanzen.Net/Finanzen.Zero
- Analysis of complex business processes and end-to-end user journeys in digital product and platform environments
- Gathering, structuring, and prioritizing business and technical requirements (Functional / Non-Functional Requirements)
- Translating business goals into actionable requirements, user stories, and acceptance criteria
- Conducting stakeholder interviews, workshops, and reviews with business teams, IT, UX, and management
- Creating and maintaining requirement artifacts (BRD, FRD, user stories, process models, decision papers)
- Ensuring consistency between business needs, technical implementation, and product vision
- Close collaboration with development teams to clarify business questions during implementation
- Support with impact analyses (A/B tests), change requests, and scope management
- Quality assurance of implemented requirements including acceptance criteria and business testing
- Advising on the further development of product strategy and roadmap structure
- Prioritizing backlog items based on business value
- Defining and sharpening product goals, KPIs, MVP definition, and other success metrics
- Evaluating new features, tools, and initiatives from a user and business perspective
- Facilitating decision-making between business, product, and technology
- Supporting go-to-market considerations and product positioning
- Sparring partner for product and stakeholder decisions at management level
- Dashboard creation, data modeling, BI report administration, and data analysis in Power BI
Qaiser Abbasi
Last position:
Freelance Lead DevOps Engineer at Schwarz Gruppe Produktion
Bootstrapping a CloudOps team and building a multi-cloud provider backend for a low-code Internal Developer Platform (IDP) with env zero
Introducing user story mapping, ADRs, milestones, and backlog management
Designing and developing core APIs, setting up CI/CD pipelines, OpenTofu/Terraform scripts
Representing and communicating the team with third-party stakeholders (e.g. env zero)
(Cross-)team coaching on DevOps, software design, Terraform, Golang, and agile practices
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.
Mehmet Fatih Sönmez
Last position:
Online Simulation Based Digital Twin Software Developer at BAM - Federal Institute for Materials Research and Testing
- Contributed to development of an online simulation-based digital twin of bridge infrastructure project.
- Created packages implementing computational and statistical modules for the digital twin.
- Modeled the structure using FEniCSX within a Python environment.
- Integrated real sensor data with the virtual model via APIs.
- Used inference models to predict the future state of the bridge.
Mohamed Ghassen Brahim
Last position:
Lead / Principal Cloud, AI & Security Architect at Freelancer / CC Conceptualise GmbH
Projects:
Project: RWE – Development of a company-wide Zero Trust cybersecurity architecture (CITADEL) Role: Senior Enterprise Cybersecurity Architect / Zero Trust Architect Company: RWE AG Description: Concept and implementation of the strategic CITADEL cybersecurity target architecture at RWE, based on the Zero Trust architecture principle and aligned with regulatory requirements such as NIS2, ISO 27001 and company-wide security governance policies. The goal was to build a measurable, auditable and scalable security architecture with a strong focus on Identity Governance, compliance transparency and operational manageability. Responsibilities & Achievements:
- Zero Trust architecture design: Developed a company-wide Zero Trust reference architecture (Identity, Device, Network, Application, Data) including trust zones, control points and enforcement mechanisms according to NIS2.
- Identity & Access Governance (IGA): Designed and introduced IGA governance structures including role models, recertification processes, segregation of duties (SoD) and lifecycle management for identities and access.
- Security governance & KPIs: Defined and implemented security KPIs and metrics to manage Zero Trust maturity, identity risks and compliance at the management level.
- Compliance & reporting: Built standardized compliance reports and dashboards to support internal audits, external assessments and regulatory evidence (e.g. NIS2).
- Architecture & stakeholder alignment: Worked closely with Enterprise Architecture, IT operations and business units to integrate the CITADEL architecture into existing IT and security landscapes.
- Strategic security consulting: Advised programs and projects on Zero Trust compliance, identity centricity and regulatory requirements in the energy and critical infrastructure (KRITIS) environment. Technologies & Methods: Zero Trust Architecture, NIS2, Identity Governance & Administration (IGA), IAM, RBAC, SoD, Entra ID, SailPoint, Zscaler, Terraform / IaC, Policy as Code, security KPIs, compliance reporting, NIST 2.0, ISO 27001, Enterprise Security Architecture, governance frameworks, risk & control management
Project: Scalable AI Workbench Platform on Microsoft Azure Role: Cloud Architect & Engineer Company: Siemens Energy Description: Design, development and operation of a secure, modular cloud infrastructure to support Data Science, Machine Learning and AI applications for various engineering teams at Siemens Energy. Responsibilities & Achievements:
- Cloud architecture: Designed and implemented an Infrastructure-as-Code solution (Terraform) for automated provisioning of Azure resources (Resource Groups, Storage Accounts, Cosmos DB, Application Insights, networking, PostgreSQL Flexible Server, Azure Container Apps, Azure Container Registry).
- Developer portal: Used Backstage with custom frontend and backend plugins (Node.js, TypeScript, React.js, PostgreSQL, Container Apps) to enable self-service and empower developers, data scientists and AI/ML engineers.
- Role-based access control: Implemented Azure RBAC to grant targeted access (e.g. Storage Blob Data Contributor, Reader) to engineering groups (e.g. AI Engineers) for relevant resources.
- Data platform engineering: Built and configured a multi-layered storage landscape (Raw, Curated, Vector data), including automated container creation and access control for advanced analytics and AI workloads.
- DevOps integration: Integrated with Azure DevOps for CI/CD pipelines to automate deployment, monitoring and compliance.
- Security & compliance: Implemented Private Endpoints, network policies and Managed Identities to ensure data protection and regulatory compliance.
- Collaboration: Worked closely with cross-functional teams to align the cloud infrastructure with business and technical requirements and drive digital transformation at Siemens Energy. Technologies: Azure, Terraform, Azure DevOps, Cosmos DB, Application Insights, Azure Storage, Private Endpoints, Azure Synapse, Azure Machine Learning, Azure Entra ID, RBAC, Backstage, Node.js, React.js, PostgreSQL, Python (automation), Git
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.
Ines Rahrah
Last position:
Entrepreneur at ZuManAsha
- Built and operated a successful handmade tray business sold via Etsy and Spock, fulfilling 120+ orders and maintaining 5-star customer reviews.
- Managed 100% of the operations including product design, international shipping, and marketing across Instagram, TikTok, and Etsy, growing a global customer base.
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.
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.
Kaan Dönmez
Last position:
IT Consultant at Tensora GmbH
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
Sanket Thakur
Last position:
Master of Engineering: Information and Electrical Engineering at Hochschule Wismar
Discover over 15,000 top freelancers
Statistics of experts using Jupyter
Aggregated from the professional profiles of matched freelancers.
Experience
11 years (Germany: 15 years)
Position duration
2.1 years (Germany: 2.9 years)
Positions per freelancer
8 (Germany: 9)
Top business areas
Information Technology, Product Development, 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% (Germany: 98%)
Master's degree or higher
81% (Germany: 80%)
Doctorate
19%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 99%)
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 Jupyter
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
Notebook work
Jupyter is an interactive environment for code, notes, charts, and results in one place. Companies use it for data exploration, reporting, model work, and shared analysis. It is often called Jupyter Notebook or JupyterLab, and many teams still refer to the older IPython Notebook name.
Where it fits
Jupyter is common in data science, research, analytics, and machine learning work. It helps specialists test ideas quickly, document steps, and turn an analysis into something others can review. It also works well for internal tools, demos, and training material.
Typical deliverables
- Reproducible notebooks for analysis and reporting
- JupyterLab environments for team use
- Data exploration workflows with pandas and NumPy
- Model prototyping and experiment tracking
- Teaching material and technical walkthroughs
Skills around it
Strong Jupyter professionals know Python, data libraries, and how to structure notebooks so they stay clear and reusable. They understand kernels, environments, package setup, and how to avoid notebook chaos. Good practice also includes version control, clean outputs, and handoff-friendly documentation.
When to bring in help
Bring in freelance specialists when notebooks are slow to maintain, hard to share, or tied to one person’s setup. They are also useful when a team in Berlin needs support for local research, analytics, or product work while other stakeholders collaborate remotely. That mix often needs clear English notebooks and careful communication.
What good looks like
- Clear notebook structure and naming
- Reliable environments and dependency management
- Clean code cells with useful narrative text
- Outputs that are easy to review and rerun
- Smooth handoff from exploration to production code
Frequently asked questions
Not sure where to start with Jupyter? These answers cover the essentials.
Jupyter is used for interactive coding, data exploration, reporting, and model prototyping. It is a strong fit when teams need code, notes, and results together in one place. Many companies also use Jupyter Notebook or JupyterLab for internal analysis that must be easy to review.
Jupyter Notebook is the classic single-document experience, while JupyterLab offers a fuller workspace with file browsing, multiple tabs, and more room for day-to-day work. For most new projects, JupyterLab is the better default. A good specialist will still know both and choose based on the workflow.
Jupyter is better for exploration, communication, and step-by-step analysis. Plain scripts are often better for automation, repeatable jobs, and production services. The best experts know when to stay in notebooks and when to move the logic into modules or pipelines.
A strong Jupyter specialist usually works with Python, pandas, NumPy, plotting tools, and Git. For machine learning work, experience with scikit-learn or notebooks that feed into ML workflows is useful. Environment management and clean documentation matter just as much as coding speed.
Jupyter work can look simple, but the hard part is keeping notebooks clean, reproducible, and easy to hand over. Small exploration tasks may need only light support, while shared analytics, research, or model work needs someone who has handled real team workflows. The right level depends on how important reuse and review are.
Yes, JupyterLab and shared notebook workflows work well with remote teams when the setup is clear. Good specialists document environment steps, keep notebooks readable, and agree on file handling early. In Berlin, teams often mix on-site discussions with remote delivery, which makes that discipline even more useful.
Look for notebooks that are easy to rerun, easy to read, and easy to extend. A strong IPython Notebook or Jupyter expert explains choices clearly, keeps dependencies under control, and avoids hidden steps in cells. Good handoff quality is usually a better sign than flashy visuals.
Companies often bring in Jupyter help when notebooks have become messy, slow, or difficult to share. Other common triggers are unreliable environments, unclear analysis steps, and a need to turn exploratory work into something the team can trust. If the output must support decisions, quality matters more than speed alone.
The average hourly rate of freelancers in Berlin, Germany who have used Jupyter in their recent projects is 79 €, which corresponds to a daily rate of about 632 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Jupyter in their recent projects, 100% hold at least a Bachelor's degree, 81% hold at least a Master's degree, and 19% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Jupyter 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 Berlin, Germany who have used Jupyter in their recent projects are German (100%), English (100%), and French (31%).
The most common industries among freelancers in Berlin, Germany who have used Jupyter in their recent projects are Information Technology (75%), Education (50%), and Healthcare (44%).
The most common business areas among freelancers in Berlin, Germany who have used Jupyter in their recent projects are Information Technology (88%), Product Development (88%), and Research and Development (81%).
Main locations of FRATCH Experts, who have recently used Jupyter
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.
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