Artificial Neural Network Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used Artificial Neural Network
Bardiya B.
Last position:
Data Scientist at Rewe Digital GmbH
Statistical Forecasting Algorithm
- Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
- Migration from R/On-premise to Python/Snowflake
- Productionalization on Snowflake in cooperation with data engineers & DevOps
Monitoring Dashboard
- Data engineering for preparation & provisioning of necessary data/resources on Snowflake
- Development & deployment of a Streamlit dashboard in Snowflake
ML-based Probabilistic Forecasting on Vertex AI
- Development of a ML-based probabilistic forecasting algorithm from scratch
- Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI
Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow
Harsh Vardhan A.
Last position:
System and Process Integrator 2 at Audi AG
Spearheaded the development and deployment of a Generative AI solution tailored for the automotive industry focusing on improving customer experience through AI-driven innovations.
Conducted in-depth market research to understand unique challenges and opportunities within the automotive sector by analyzing industry trends, customer pain points, and competitive offerings to inform the product strategy.
Formulated a strategic vision for the Generative AI solution targeting personalized customer experiences, aligned product vision with the company’s long-term goals and automotive market demands.
Enhanced customer satisfaction by introducing personalized AI-driven features, achieving a 15% increase in customer engagement and loyalty.
Attended and represented Audi AG on a group-wide level in workshops for AI strategy for customer experience.
Leveraged knowledge of recurrent neural networks and transformer architecture.
Utilized GPT-3 generative AI frameworks.
Employed TensorFlow and PyTorch for machine learning.
Used Tableau from Salesforce for data analysis and visualization.
Served as solution manager for the Business Architecture team.
Collaborated with business stakeholders within Audi OEM to gather requirements for CRM strategy including marketing department, CRM heads across countries, VW group brands and CARIAD SE.
Represented Audi AG in CRM strategy workshops held in different countries.
Discussed CRM strategy with head of CRM and Data based on workshop outcomes.
Conducted business analysis on gathered market data to improve customer experience.
Planned and launched marketing campaigns such as welcome mailing, license renewal reminders, Audi Progress Circle and Black Friday campaigns.
Managed project budget.
Acted as solution manager for the ONE.CRM team at CARIAD SE on loan from Audi AG.
Collaborated with business owners of VW group brands to develop a central solution.
Represented CARIAD SE in CRM strategy workshops in Spain, France and Italy.
Discussed CRM strategy with head of CRM at CARIAD SE based on workshop outcomes.
Conducted business analysis on market and brand data to improve customer experience.
Planned and delivered campaign capabilities from template to brands such as welcome mailing for Audi AG, SEAT and SKODA.
Managed project budget together with head of CRM.
Mathew D.
Last position:
Data Science Expert and AI Strategist at Freelancer
- Built an API to ingest, clean, translate, and index EU tenders documents in Neo4j, enabling hybrid search with RAG and Cypher queries via a Streamlit dashboard
- Deployed the API on AWS Lightsail container services with CI/CD automation via GitHub Actions, ensuring stability through pytest unit and integration tests
- Designed and developed a comprehensive online course on data analysis using ChatGPT for professionals and learners, creating instructional videos and interactive Jupyter notebooks
- Utilized OBS and professional audio equipment to ensure high-quality video and audio content
- Led a CRM data normalization and cleaning project visualized via a Sankey diagram to aid customer understanding and pipeline development
- Implemented and validated a genAI-driven web crawling strategy on AWS, ensuring data quality, scalability, and CRM data augmentation
Garima C.
Last position:
IT Program Director at Trax Retail
- Directed global IT teams in implementing cloud-based, AI-driven solutions, aligning with customer requirements through comprehensive data migration strategies
- Led cloud migration initiatives from legacy systems to scalable cloud platforms, streamlining data handling through API-driven processes to enable real-time analysis and reporting
- Enhanced reporting accuracy and customer satisfaction using machine learning and neural networks, achieving 97% classification accuracy
- Advanced projects using augmented reality (AR) to optimise user experience and meet client goals
Yevgeniy Ö.
Last position:
Tester, Test & Data Analyst at NORD/LB
- Analyze system requirements and mapping concepts (ETL requirements) for data flows and transformation logic in the bank's DWH
- Analyze data in DB tables and views of the DWH using SQL (DB2)
- Independently define, create, and execute test cases in JIRA Xray (SIT)
- Write SQL queries in DB2 to verify data scenarios and mappings
- Create test plans for SAP FSDP and concurrent projects
- Conduct error and root cause analyses in coordination with business analysts, developers, test managers, and the infrastructure team
- Thoroughly document test results in JIRA Xray
- Coordinate between business analysis, development, DB infrastructure, business units, and external vendors
Kevin M.
Last position:
Freelance Lecturer in Coaching at DSI Education GmbH
- Practice-oriented coaching on core aspects of data science
- Teaching advanced concepts in Python as well as automation (with Make and n8n) and ETL processes with Apache Airflow
- Weekly preparation and delivery of practice-oriented programming courses using real-world examples
- Promoting practical programming skills among participants through interactive exercises and individual support
- Developing didactic materials and adapting content to participants' skill levels
- Close collaboration with the team for continuous improvement of course quality and learning outcomes
Discover over 15,000 top freelancers
Statistics of experts using Artificial Neural Network
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 16 years)
Position duration
2 years (Germany: 2.3 years)
Positions per freelancer
8 (Germany: 10)
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Pharmaceutical
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
100% (Germany: 99%)
Master's degree or higher
83% (Germany: 88%)
Doctorate
33% (Germany: 30%)
Certifications per freelancer
6 (Germany: 2)
Most common languages
English, German, French
Speak two or more languages
83% (Germany: 98%)
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Frankfurt are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Frankfurt using Artificial Neural Network
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 16 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Artificial Neural Network 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 (83%)
- Banking and Finance (67%)
- Pharmaceutical (50%)
- Professional Services (50%)
- Retail (50%)
- Automotive (33%)
- Education (33%)
- Healthcare (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it is
An Artificial Neural Network is a machine learning model inspired by connected biological neurons. It learns patterns from labelled or unlabelled data through layers of weighted connections, then produces predictions, classifications or generated outputs. The common abbreviation ANN is often used in technical discussions.
What it builds
Artificial Neural Networks support software that can interpret complex data and respond to changing inputs. Typical deliverables include:
- Image, video and document recognition
- Demand forecasting and anomaly detection
- Recommendation and ranking systems
- Speech and natural language features
Ecosystem and tooling
Professionals work across Python data stacks, notebook environments and production services. Common tools include PyTorch, TensorFlow, Keras, scikit-learn, NumPy and pandas. Strong delivery also involves data labelling, feature preparation, experiment tracking, model serving, containerisation and cloud infrastructure.
When expertise matters
Companies bring in freelance specialists when a proof of concept must become a reliable product, internal data is difficult to use or model performance has stalled. Expertise is also valuable when teams need a clear training pipeline, reproducible experiments or an efficient way to run inference in an existing application.
- Data quality and labelling need structured review
- Training results are difficult to reproduce
- A model must run securely in production
Frankfurt collaboration
Frankfurt companies in finance, logistics, manufacturing, healthcare and commerce can apply neural models to documents, transactions, operations and customer interactions. Local specialists can support workshops and on-site coordination, while remote professionals can contribute through shared repositories, experiment logs and documented handovers. German and English collaboration should be agreed early.
Strong professionals
The strongest specialists understand both model behaviour and business constraints. They select a suitable architecture, establish meaningful validation, manage overfitting and explain trade-offs clearly. They also monitor drift, latency, privacy and infrastructure costs after deployment instead of treating training as the final deliverable.
Frequently asked questions
Before you brief your next project: the most common questions about Artificial Neural Network.
An Artificial Neural Network learns relationships in data and uses them to classify, predict or generate results. Companies use ANNs for computer vision, forecasting, recommendation, fraud detection, speech processing and language features.
An Artificial Neural Network can learn complex representations directly from large or unstructured datasets, while methods such as linear models, decision trees and gradient boosting can be easier to interpret and train on structured data. The right choice depends on data volume, explainability, latency and the business outcome.
A strong ANN specialist usually understands Python, data preparation, statistics, SQL and model evaluation. Production work may also require PyTorch or TensorFlow, API design, cloud services, containers, monitoring and responsible handling of sensitive data.
An Artificial Neural Network proof of concept may suit a specialist who has delivered comparable experiments and can validate assumptions carefully. A production system calls for broader experience with data pipelines, deployment, monitoring, failure modes and communication with domain experts.
Yes. Artificial Neural Network work is often suitable for remote collaboration when data access, environments and decision ownership are clearly organised. Frankfurt teams should define expectations for on-site workshops, German or English communication, repository access and secure handling of datasets.
Assess whether an Artificial Neural Network is tested against a relevant baseline and evaluated on data that reflects real usage. Look for clear error analysis, reproducible training, suitable validation, documented limitations and monitoring plans rather than relying on one performance measure.
An Artificial Neural Network may be unsuitable when the dataset is small, the decision must be highly transparent or a simpler model already meets the requirement. A careful specialist should compare alternatives, including rules, statistical models and tree-based methods, before recommending neural modelling.
An ANN professional should clarify the target outcome, available data, labels, acceptance criteria, deployment environment and ownership of the trained model. They should also ask about privacy constraints, retraining expectations, integration points and who will maintain the system after handover.
The average hourly rate of freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects is 108 €, which corresponds to a daily rate of about 863 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects, 100% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 33% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects are English (100%), German (83%), and French (33%).
The most common industries among freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects are Information Technology (83%), Banking and Finance (67%), and Pharmaceutical (50%).
The most common business areas among freelancers in Frankfurt, Germany who have used Artificial Neural Network in their recent projects are Information Technology (100%), Business Intelligence (83%), and Product Development (83%).
Main locations of FRATCH Experts, who have recently used Artificial Neural Network
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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