<h3><strong>About us:</strong></h3> <p> </p> <p>Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction. 🙂</p> <p>Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfill their dreams and objectives.</p> <p>Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.</p> <p><br/> </p> <h3><strong>The Role:</strong></h3> <p> </p> <p>We are looking for a Senior Data Scientist (Python) to join one of our high-growth client teams as a technical lead in data innovation. In this role, you will be responsible for transforming complex, high-velocity datasets into predictive models and actionable systems that directly influence product strategy and business operations.</p> <p>You will bridge the gap between pure research and production software engineering. You will not just build prototypes in notebooks; you will design, train, evaluate, and deploy robust machine learning models into live cloud environments. This is a role for a systems-thinking data scientist who values clean, modular Python architecture, statistical rigor, and scalable data pipelines.</p> <p> </p> <h4><strong>What we are looking for:</strong></h4> <ul> <li>5+ years of professional experience as a Data Scientist, with expert-level mastery of the Python data ecosystem (Pandas, NumPy, SciPy, Scikit-Learn).</li> <li>Deep theoretical and practical knowledge of supervised and unsupervised learning, regression, classification, clustering, and time-series forecasting.</li> <li>Proven track record of moving models out of Jupyter Notebooks and into production environments using containerization (Docker) and microservice design.</li> <li>Strong proficiency in writing complex, optimized SQL queries and experience handling large-scale data using distributed computing frameworks like PySpark or Ray.</li> <li>Experience with machine learning lifecycle tools (such as MLflow, DVC, or Weights &amp; Biases) for model tracking, versioning, and feature store management.</li> <li>Hands-on experience leveraging cloud data infrastructure (AWS, GCP, or Azure) and managed ML services (e.g., SageMaker or Vertex AI).</li> <li>Time zone: CET (+/- 3 hours). We are unable to consider applications from candidates in other time zones.</li> </ul> <p> </p> <h4><strong>Nice-to-have:</strong></h4> <ul> <li>Deep Learning experience using PyTorch or TensorFlow/Keras.</li> <li>Experience with NLP frameworks (Hugging Face, spaCy) or deploying LLM-based pipelines (LangChain, vector databases).</li> <li>Familiarity with