Hire the Top 2% of
Freelance Data Science Developers
in Germany

Akshat (.

Data Science developer in Germany (UTC+1)

Seasoned machine learning engineer and researcher with 5+ years of experience leveraging deep learning and NLP to make computers intelligent. Skilled in computer vision, speech processing, language understanding, GANs, and cloud model deployment.

Sanja J.

Data Science developer in Germany (UTC+2)

Senior Data/Machine Learning Scientist with a strong foundation in scientific research and extensive experience applying machine learning in the business industry. Proven expertise in leading end-to-end projects, building scalable ML systems (including MLOps), and driving impactful business solutions through predictive analytics. Specializes in research, explainable AI and Bayesian modeling, with proficiency in different ML frameworks. Recognized for innovative problem-solving and fast learning.

Sebastian N.

Data Science developer in Germany (UTC+2)

* Over 5 years of experience as a Data Scientist and AWS Cloud Engineer * Trained and prototyped over 20 Machine Learning models for various AI use cases and clients * Led deployment of two ML models at scale on the AWS Cloud, earning the WirtschaftsWoche Best of Consulting Technology Award 2020 * Experience in diverse areas: Data Security in ML, AI-driven Drug Design, Named-Entity Recognition, Predictive Maintenance, GenAI and more * Led the development of two AI Platforms for enterprise clients, streamlining ML deployments and operations

Fenosoa R.

Data Science developer in Germany (UTC+2)

I am a Data Scientist with experience in mitigating greenhouse gas emissions, transfer learning, and developing predictive models. I hold a Master's degree in Machine Intelligence and have expertise in Python, Pytorch, TensorFlow, and SQL.

Christian N.

Vetted Data Science developer in Germany (UTC+2)

I have a background in theoretical physics and have worked on machine learning and data science-related topics since 2016. Since then, I have published multiple peer-reviewed papers on machine learning as part of the autonomous driving unit at Mercedes Benz AG and worked as a data science consultant/developer for DAX-listed companies. Others would describe me as creative in my thinking, excelling at finding new ways to tackle problems. I love intellectual challenges that keep me engaged and thrive in cooperative working environments. I am a very self-directed person who can quickly identify what needs to be done and act accordingly. On top of that, my strengths are communicating complex ideas at an appropriate level and holding engaging presentations.

Mohamed A.

Data Science developer in Germany (UTC+1)

I am a skilled ML Engineer with experience in client interactions, project lifecycle management, and model development. Proficient in Python, Pytorch, and various AI technologies. Award-winning and top-rated on Upwork.

Aiden E.

Vetted Data Science developer in Germany (UTC+1)

Looking for new adventures and challenges! A seasoned Senior Data Scientist and Machine Learning Engineer, with 5+ years of expertise in advanced text and statistical analytics, ML, statistical modeling, and NLP applications. Skilled in extracting insights from complex datasets to drive data-driven decision-making. Proficient in programming languages like Python, SQL, and Java and tools like GCP, and AWS. Exceptional problem-solver, adept at teamwork, and effective communication skills. Seeking a role as a Machine Learning Engineer, Data Scientist, Data Engineer, or Data Analyst. - \- Open to Relocate (in Germany) \## Skills Summary \# Technical Proficiency \- Programming Languages and Frameworks: Advanced proficiency in Python, Flask, and Java for full-stack Machine Learning development. \- AI/ML Technologies: Hands-on experience applying classification, regression, clustering, deep learning, image processing, and NLP techniques to solve real-world problems. \- Libraries: Expertise in NumPy, Pandas, PySpark, TensorFlow, Keras, PyTorch, sci-kit-learn, OpenCV, SciPy, SpaCy, Matplotlib, Seaborn, and Plotly for data exploration, modeling, and visualizations. \- Cloud Technologies: Extensive experience architecting and deploying end-to-end data science solutions on AWS (SageMaker, EC2, Lambda, S3) and GCP (Vertex AI, Compute&App Engine) platforms. \- Databases: In-depth working knowledge of SQL, MySQL, PostgreSQL, BigQuery, MongoDB, and Spark for efficient data storage, manipulation, and querying large datasets. \- Data Science and Misc. Technologies: Hands-on with generative AI, large language models, mathematics, time series analysis, recommendation engines, NLP applications, and Jupyter Notebook. \- Deployment/MLOps: Expertise using MLFlow, Airflow, FlaskAPI, TensorBoard, CI/CD, and Agile methodologies for robust model operationalization. \# Soft Skills \- Communication: Strong presentation skills to report influential findings to technical and non-technical stakeholders. \- Problem-Solving: Critical thinking and analytics to address challenging problems methodically. \- Collaboration: Proven team player with the ability to build consensus and achieve group objectives. \- Business Acumen: Track record of strategic business recommendations by translating complex analytics into actionable insights. Continuous Learning and Adaptability \- Innovation Mindset: Passion for self-improvement and hands-on experience with emerging technologies. \# Ethics & Compliance \- Data Privacy: Knowledge of data privacy, ownership, and ethical use as per regulatory standards like GDPR, and CCPA. \- Compliance: Understanding of legal frameworks to ensure projects meet quality and security compliances.

David L.

Data Science developer in Germany (UTC+1)

🔯 Data Engineer / Reliability Engineer ⚛️ Scalable Data Products ☸️ MLOps ft. Kubernetes * Full-Stack Machine Learning Engineer capable of realising ML projects end-to-end (MLOps, NLP, Time Series, Deep Learning, Explainable AI). * DevOps and Cloud Engineer capable of designing and implementing fully auto-scaling, cloud-native Data Processing Architectures (Kubernetes, Knative, Helm, IaC, DevOps, GitOps). * Designing and building Python based Data Architectures (distributed, parallel, concurrent) in full remote self-organizing Scrum & Kanban teams for 6 years. * Extensive experience with Open-Source Intelligence, Supply Chain Intelligence, and Scientific & Industrial Big Data. * Team-player, mentor, eager to grow, morally ambitious.

Nidhi J.

Data Science developer in Germany (UTC+1)

I am an AI/Machine Learning Engineer with experience in designing and implementing rover systems, leading AI projects, and deploying models on NVIDIA Jetson devices. I have also worked as a Software Engineer and Application Engineer, showcasing expertise in developing CNN models, hosting Django servers, and optimizing system performance. My educational background includes a Master's in Information Technology and a Bachelor's in Engineering, with coursework in Deep Learning, Machine Learning, and Robotics. My skills include Python, C++, TensorFlow, OpenCV, and Linux.

Wasim A.

Data Science developer in Germany (UTC+1)

Collaborations: Participated and drove interdisciplinary, collaborative projects, resulting in multiple publications in top-tier science journals. Problem-solving: Solved complex problems across diverse domains using numerous programming languages, statistical methods, and machine learning (Bayesian analysis, predictive analytics, deep learning, NLP); significantly enhanced biomedical information retrieval when compared to state-of-the-art methods. Web & Desktop App Development: Developed end-to-end software implementations by integrating backend and front-end components. Biomedical Data Science: Expertise in genomics, proteomics data analysis, and biomedical data integration. Developed R packages, Shiny, and Electron apps used by 10+ labs. Applied prompt engineering on LLMs to construct knowledge graphs, enhancing biomedical information retrieval and domain-specific QA. Generative AI Application Development: Developed and deployed web apps using GenAI technologies to facilitate biomedical information retrieval. Application Deployment: Deployed web applications on DigitalOcean droplets and local lab machines; experimenting with AWS and Kubernetes for cloud computing.