Data Science Experts in Berlin
from over 15,000 CVs with fast, precise AI matchingHire experts who turn complex data into reliable forecasts, customer insights and decision-ready products. Work with specialists in Python, R, SQL, machine learning and cloud data workflows, matched quickly with vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Data Science
Dmitry P.
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.
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.
Deepak M.
Last position:
Lead ML Platform Engineer at Billie GmbH
- Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
- Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
- Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
- Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
- Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
- Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
- Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
- Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
- Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
- Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices
Haseeb Z.
Last position:
Senior Data Scientist at WPP MEDIA
- Designed and deployed enterprise Retrieval-Augmented Generation (RAG) applications using LangChain, LangGraph, vector databases, embeddings, and open-source LLMs served through vLLM on GCP GPU infrastructure.
- Built agentic AI workflows using LangGraph with planning, reasoning, tool execution, persistent memory, session management, and Human-in-the-Loop approval mechanisms.
- Developed LLM-powered automation systems integrating BigQuery, SQL pipelines, and external advertising APIs including Meta, TikTok, Amazon, Snapchat, Google, and Pinterest, reducing manual operational workflows.
- Architected multi-agent AI systems for enterprise analytics and decision-support workflows, enabling autonomous task execution and intelligent data interactions.
- Implemented retrieval optimization strategies including multi-retriever architectures, semantic search, context optimization, and query improvement techniques, improving response relevance by approximately 40%.
- Engineered structured prompting strategies, function-calling schemas, and validation workflows to improve reliability of multi-step LLM applications.
- Designed scalable AI services using Python, FastAPI, Cloud Run, Pub/Sub, BigQuery, Docker, and cloud-native deployment architectures.
Sejal V.
Last position:
Data & ML Engineering at Consulting
- Fractional leadership; consulting growth-stage startups and scale-ups on data strategy, ML products, and platform foundations
- Building decisioning systems for growth, personalization, & product experimentation, across e-Commerce, Digital Health, Energy, and Logistics
- Exploring Agentic AI & LLM-based tooling for production readiness patterns
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
Muzamal A.
Last position:
Data Scientist / AI Consultant at HelmX
- Delivered AI and data science solutions, including LLM-based chatbots and data pipelines, improving operational efficiency.
- Collaborated on product features, achieving measurable impact and maintaining strong client relationships.
Birte L.
Last position:
Product & Agile Consultant at self employed
- Support teams, companies and individuals to become excellent Product Managers
- Build up the right organization to create customer and business value
Marc F.
Last position:
Interim Talent Acquisition Manager at doctari
- Building a cross-functional product team to develop a super app
- Advising and mentoring to support the team and provide input (technical & soft skills)
Raphael M.
Last position:
Founder / Quant Developer at Market Maker
- Crypto quant strategy development, automated trade execution, onchain data client (Ethereum / Solana)
- Data and trade architecture development for liquidity provision
Mathias W.
Last position:
Implementation of an on-premise OCR solution with information extraction at Mindhopper GmbH
- Insurance service provider*
Challenge: Business-critical documents were processed through external OCR providers, with ongoing costs, dependency, and data privacy risks for sensitive insurance data.
Implementation:
- Architecture and production implementation of an on-premise OCR solution with full data ownership
- Methods for recognizing document structures as the basis for automated further processing
- ML-, NLP-, and LLM/VLM-based information extraction, especially from invoices and quotations
Success: Replaced external providers: full data ownership, GDPR-compliant processing, and 75% lower recurring OCR costs per year
Used technologies: Python, Docker, Microservices, FastAPI, PyTorch, Torchvision, MongoDB, MySQL
Nikunjkumar P.
Last position:
Senior Java Backend Developer at Questax Professionals GmbH
- Provide the Price Listing Service team with prices for all cars and vans in different markets
- Adapt market-specific requirements such as taxes, government subsidies, campaigns
- Import and synchronize new prices for all new and existing cars and store them in the Redis datastore
- Support our product and on-call duty
- Daily business, development of new features, bug fixing
- Pair programming, code review, mob programming
- Develop POCs for new ideas
- Maintain and extend the backend
- DevOps tasks
- Run Kubernetes updates
- Adjust and further develop Kubernetes resources
- Develop and adapt Helm charts
- Adapt and update ArgoCD
- Maintain, adapt, and improve CI/CD
Yahya S.
Last position:
Odoo Software Developer & Consultant at KNAUER Wissenschaftliche Geräte GmbH
- Planning and implementing tailored Odoo ERP solutions to support and optimize specific business processes
- Configuring and customizing Odoo modules according to individual customer requirements, including process automation and data integration
- Training and supporting end users and administrators to ensure full use of Odoo features and to enhance user skills
- Providing ongoing post-implementation support, including troubleshooting, maintenance and updates to adapt to new business requirements
- Migrating data and integrating external applications into Odoo environments for a seamless, unified data landscape
- Analyzing and improving existing Odoo systems to boost efficiency and optimize the user experience
Nino S.
Last position:
Freelancer in Data Science at International Companies
Proceeding what was started in 10/2023, offering data science development skills fulltime to international clients
Helping companies learn more about their existing (unstructured) data, optimize processes and technical systems, and derive solutions for their problems
Tools and technology used: Python (sklearn, pandas, numpy, Django, sqlAlchemy, pyTorch), Matlab, Docker, AWS EC2, Lambda, S3, SQL, MySQL, Hadoop & Spark, Machine Learning, DNN, AI, Jira, Confluence, Git, CI/CD, GitLab, Jenkins
Louis G.
Last position:
Freelance Solutions Architect and Machine Learning Engineer at Self-employed
- Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
- Work with customers to understand their challenges and provide the best solutions based on open-source data products
- Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
- Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
- Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
- Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
- Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
- Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible
Discover over 15,000 top freelancers
Statistics of experts using Data Science
Aggregated from the professional profiles of matched freelancers.
Experience
13 years (Germany: 14 years)
Position duration
2.2 years
Positions per freelancer
8 (Germany: 9)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Education, Professional Services
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
79% (Germany: 80%)
Doctorate
21% (Germany: 22%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
English, German, Spanish
Speak two or more languages
93% (Germany: 97%)
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 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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Data Science 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%)
- Education (50%)
- Professional Services (50%)
- Retail (34%)
- Automotive (31%)
- Healthcare (31%)
- Media and Entertainment (29%)
- Banking and Finance (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
From data to decisions
Data Science combines statistics, programming and domain knowledge to extract useful signals from structured and unstructured data. Companies use it to forecast demand, detect anomalies, personalise experiences, optimise operations and support decisions with measurable evidence. The work can range from exploratory analysis to production machine learning services.
Core methods
Strong specialists choose methods that fit the question, data quality and operational constraints. They frame hypotheses, clean and join data, select meaningful features, validate models and explain uncertainty. Common approaches include regression, classification, clustering, time-series forecasting, recommendation systems and natural language processing.
Tools and delivery
The ecosystem often centres on Python or R, with SQL for data access and notebooks for exploration. Specialists may work with pandas, NumPy, scikit-learn, Jupyter, PyTorch or TensorFlow, alongside cloud warehouses, workflow orchestration, containerisation and model monitoring. Production delivery requires reproducible pipelines, version control, testing and clear documentation.
Where companies use it
Data Science supports products and internal processes across Berlin’s technology, mobility, finance, retail, healthcare and industrial sectors. Typical assignments include:
- Demand, revenue and capacity forecasting
- Customer segmentation and churn analysis
- Fraud, risk and anomaly detection
- Recommendation and search improvement
- Experiment analysis and decision dashboards
When freelance expertise helps
Companies bring in freelance specialists when a new use case needs rapid validation, an internal team lacks a specific modelling skill or a prototype must become a dependable service. Clear signs include fragmented data, weak measurement, unclear model ownership or a growing need for MLOps. In Berlin, remote work is common, while on-site sessions can help with discovery, workshops and stakeholder alignment.
What strong specialists deliver
The best professionals connect business goals with technical choices instead of treating model accuracy as the only outcome. They define useful success criteria, establish trustworthy data checks, compare sensible baselines and communicate limitations without obscuring them. They also leave behind maintainable code, transparent documentation and a practical plan for monitoring drift and retraining.
Frequently asked questions
What clients ask us most about Data Science — answered in short.
Data Science helps companies turn data into forecasts, explanations, recommendations and automated decisions. A specialist can support use cases such as demand planning, fraud detection, customer retention, quality control and product personalisation.
Data Science often goes beyond reporting what happened by modelling what may happen next or what action could improve an outcome. Business intelligence and analytics remain important for dashboards, reporting and descriptive analysis, while data science adds statistical modelling, experimentation and machine learning where they are useful.
A strong Data Science freelancer usually combines Python or R with SQL, statistics, data visualisation and cloud data tools. Experience with software engineering, machine learning operations, experiment design and communication helps move work from a notebook into a reliable business process.
The right Data Science experience depends on the assignment, not on a fixed career threshold. An exploratory analysis may need strong statistics and domain understanding, while a production model also requires data pipelines, deployment, monitoring, security and ownership after launch.
Data Science work is often well suited to remote collaboration because data access, notebooks and code reviews can be managed online. Berlin teams should agree early on access controls, documentation, meeting language, working hours and the occasions when on-site workshops add value.
Evaluate whether the Data Science specialist understands the business decision behind the model and tests assumptions against realistic data. Look for reproducible analysis, sensible baselines, careful validation, clear explanations of uncertainty and a plan for deployment and monitoring.
Data Science should not default to machine learning. If a clear rule, statistical test or well-designed dashboard answers the question, that may be the better choice; machine learning becomes valuable when patterns are complex, predictions must scale or decisions can improve through feedback.
Before starting Data Science work, clarify the decision to improve, available data, legal and access constraints, delivery environment and who owns the result. Agree on evaluation criteria, stakeholder responsibilities and how the model or analysis will be maintained after handover.
The average hourly rate of freelancers in Berlin, Germany who have used Data Science in their recent projects is 92 €, which corresponds to a daily rate of about 738 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Data Science in their recent projects, 100% hold at least a Bachelor's degree, 79% hold at least a Master's degree, and 21% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Data Science in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Berlin, Germany who have used Data Science in their recent projects are English (98%), German (95%), and Spanish (14%).
The most common industries among freelancers in Berlin, Germany who have used Data Science in their recent projects are Information Technology (83%), Education (50%), and Professional Services (50%).
The most common business areas among freelancers in Berlin, Germany who have used Data Science in their recent projects are Information Technology (83%), Product Development (79%), and Business Intelligence (71%).
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.
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
