Data Science Experts in Nuremberg
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Meet FRATCH Experts in Nuremberg, who have recently used Data Science
Felix Kluge
Last position:
Senior Data Scientist at Novartis Pharma AG
- Led the implementation and validation of digital technology for real-world mobility assessment across clinical trials with high compliance rates
- Headed a cross-functional initiative that bridged clinical and data science teams, aligning digital technology integration with strategic goals
- Innovated algorithm development for sensor data analysis, leveraging time-series data to extract novel insights and improve predictive accuracy
- Designed and deployed predictive models using machine learning, integrating digital device data with clinical datasets
- Delivered strategic insights through the creation of dashboards and reports, ensuring effective data quality control and visualization for clinical trials
- Ensured reproducibility in data science workflows by establishing robust coding practices, comprehensive documentation, and version control
- Co-led exploratory statistical plans for digital biomarkers, advancing understanding and application of digital technologies in healthcare research
- Advised clinical teams as a subject-matter expert on digital technologies, fostering strategic integration and effective utilization in clinical trials
- Managed stakeholder engagement by collaborating with internal and external stakeholders, including contract research organizations and technology vendors
- Influenced decision-making by presenting analyses and findings to various management levels and stakeholders, emphasizing actionable insights and implications
- Disseminated knowledge through peer-reviewed publications
Pawan Saxena
Last position:
CAPTCHA Recognition using CRNN
- Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
- Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
- Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
- Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
- Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib
Uddipan Basu Bir
Last position:
Research Team Member at Munich Music Labs, TUM
- Focused on exploring the intersection of Music and AI.
Ashmi Jha
Last position:
Software Developer at Myrix Labs
- Engineered high-performance APIs with FastAPI + MongoDB, integrating live weather data (NOAA, NWS).
- Developed an AI chatbot with OpenAI APIs — context-aware by location, profession & interests.
- Created admin dashboard APIs for real-time monitoring and zero-downtime configuration.
- Integrated Stripe Embedded Payments with secure transactions & subscription management via webhooks.
Vasuraj Bhatia
Last position:
Cloud Data Analyst at Bhatia Reply
- Analyzed 50K+ customer records using SQL and Python in a cloud services firm, identifying trends
- Designed interactive Tableau dashboards for sales and marketing stakeholders, reducing report
- Developed ARIMA and AutoARIMA time series models to forecast AWS resource utilization, cutting
- Automated ETL pipelines with Python, improving workflow efficiency by 20% for scalable data
- Collaborated with DevOps teams to deploy 3 machine learning models in production using Docker
Ekaansh Khosla
Last position:
Master thesis - LLM powered RAG System at Friedrich-Alexander-Universität Erlangen-Nürnberg
- Developed a RAG system to automate student queries with 96% accuracy, built using FastAPI and LangChain and deployed on the university server with Docker.
- Evaluated performance using RAGAS, comparing LLMs (Llama3.3, Llama3.1, GPT-4o-mini), vector embeddings, and various retrieval techniques within the RAG pipeline.
- Technical Skills: Python, FastAPI, Docker, AWS, LangChain, LangSmith, NLP, HTML, CSS
Anshul Pandey
Last position:
BSc Artificial Intelligence at Friedrich Alexander University Erlangen-Nuremberg
- Current Grade: 1.4.
- Applied Programming on Signal Processing: Fourier Transform, Filtering, VisPy, and NumPy.
- FAUST WebSecurity Workshop.
- Hands-on experience in LLMs, Applied Data Science, and data analysis.
- Proficient in Python, PyQt5, C++, MS Office, Git, Pandas, NumPy, VisPy, JavaScript, CSS, Machine Learning, and HTML.
Maria Emde
Last position:
Certificate of Further Education in Data Science at IU Akademie (IU Internationale Hochschule GmbH)
- One module corresponds to a workload of 150 teaching units.
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
7 years (Germany: 15 years)
Position duration
1.4 years (Germany: 2.2 years)
Positions per freelancer
5 (Germany: 9)
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Education, Healthcare
Certification focus areas
Research and Development, Information Technology, Business Intelligence
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
71% (Germany: 78%)
Doctorate
14% (Germany: 22%)
Certifications per freelancer
1 (Germany: 3)
Most common languages
German, English, Hindi
Speak two or more languages
100% (Germany: 96%)
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 Nuremberg 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 Nuremberg using Data Science
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 it covers
Data Science brings together statistics, coding, and domain knowledge to turn raw data into useful decisions. It is used for forecasting, customer analysis, anomaly detection, and operational reporting. Common stacks include Python, R, SQL, notebooks, and cloud data tools.
Typical work
- Data cleaning and preparation
- Exploratory analysis and feature work
- Predictive models and validation
- Dashboards, reports, and KPI tracking
- Experiment design and A/B analysis
Skills that matter
Strong specialists do more than train models. They frame the business question, choose the right method, explain results clearly, and check for bias, leakage, and weak data quality. Good communication is as important as technical depth.
When companies hire
Teams bring in freelance expertise when data work needs to start quickly, when a project needs extra hands, or when an internal team lacks a specific method. This often happens for cleanup of legacy datasets, model reviews, executive reporting, or a one-off analysis with a clear deadline.
Tools and ecosystem
Data Science projects often rely on Python libraries such as pandas, NumPy, scikit-learn, and statsmodels, plus Jupyter, Git, and SQL. Depending on the stack, specialists may also work with Spark, dbt, BigQuery, Snowflake, or cloud notebooks. The right mix depends on the data source and delivery target.
Nuremberg context
In Nuremberg, Data Science work often sits close to manufacturing, logistics, retail, and industrial planning. Some engagements need on-site workshops and stakeholder sessions, while others can run fully remote. Clear German and English communication is often useful when teams, data owners, and specialists work together across locations.
Frequently asked questions
Curious about Data Science? Here are the answers that come up again and again.
Data Science is used to turn business data into forecasts, patterns, and decisions. Companies use it for demand planning, customer analysis, risk checks, process monitoring, and reporting that goes beyond simple dashboards.
Data Science goes further than classic BI because it can predict outcomes, test hypotheses, and model complex relationships. BI focuses more on descriptive reporting, while Data Science can also explain, classify, and forecast.
A strong Data Science freelancer usually combines Python or R, SQL, statistics, and clear communication. Useful adjacent skills include data engineering basics, cloud data tools, experimentation, and the ability to explain results to non-technical stakeholders.
A Data Science project does not always need a long team setup, but it does need the right depth for the task. A small analysis may only need a specialist who can clean data and deliver insights, while a predictive model or production review calls for stronger modeling and validation skills.
Bring in Data Science expertise when the internal team is busy, the problem is specialized, or the work has a tight deadline. It also helps when you need an outside view on model quality, data issues, or a one-time analysis that should not distract the core team.
Yes, most Data Science work can be done remotely because the main inputs are data, context, and regular feedback. In Nuremberg, on-site time can still help for workshops, data access discussions, or stakeholder alignment, especially when several teams need to agree on scope.
Data Science is broader than machine learning. It includes analysis, data preparation, experimentation, and decision support, while machine learning is one part of that work. If your project needs prediction or automation, you want someone who can do both the analysis and the model work well.
Look for a Data Science specialist who can explain data choices, show validation steps, and point out limits clearly. Good work is reproducible, tied to a real business question, and based on clean assumptions rather than only on impressive-looking charts.
The average hourly rate of freelancers in Nuremberg, Germany who have used Data Science in their recent projects is 58 €, which corresponds to a daily rate of about 467 € based on an 8-hour working day.
Of the freelancers in Nuremberg, Germany who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Nuremberg, Germany who have used Data Science in their recent projects have 7 years of professional experience, with a single engagement typically lasting around 1.4 years.
The most common languages among freelancers in Nuremberg, Germany who have used Data Science in their recent projects are German (100%), English (100%), and Hindi (38%).
The most common industries among freelancers in Nuremberg, Germany who have used Data Science in their recent projects are Information Technology (88%), Education (63%), and Healthcare (38%).
The most common business areas among freelancers in Nuremberg, Germany who have used Data Science in their recent projects are Information Technology (75%), Product Development (75%), and Research and Development (75%).
Main locations of FRATCH Experts, who have recently used Data Science
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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Philipp Thomaschewski
FRATCH CEO
