[Remote] Senior Data Scientist

O projekcie: At DS STREAM, we harness the power of AI, Data Science, and Cloud Solutions to drive growth and innovation for global brands. With over 180 experts and 130+ industry certifications, we deliver impactful solutions tailored to your business needs. Why join us? - Work on impactful, large-scale projects that influence real business outcomes. - Engage with a variety of data types: tabular, textual, image, and time series. - Solve complex technical problems by combining domain knowledge with advanced ML techniques. - Collaborate with a team of experts eager to share their knowledge. What we offer: - Flexible working hours, 100% remote work (in the EU)- Collaboration with experienced specialists (backend, infrastructure, AI)- Salary adequate to skills- Opportunity for further development and feature expansion If you’re looking for an exciting role in Data Science where you can make an impact and grow, we’d love to hear from you! Wymagania: Requirements: - At least 5 years of experience in Data Science, including production-level model deployment. - Proficiency in Python programming (Tensofrlow, PyTorch, Scikit-Learn) and advanced SQL skills. - Experience with large-scale data processing and ML models.- Proven track record with complex predictive modeling, recommendation systems, and optimization techniques. - Ability to translate business challenges into ML solutions.- Working knowledge of at least one public cloud environment (Azure, GCP or AWS). - Excellent communication skills, capable of presenting technical concepts to non-technical audiences. Codzienne zadania: - Build and maintain machine learning models for predictive analytics, optimization, and forecasting. - Develop recommendation systems and algorithms to support data-driven decisions. - Process and enhance datasets, including feature engineering and computer vision tasks (e.g., image analysis). - Conduct data quality audits, ensure dataset integrity, and prepare data for modeling. - Design and run proof-of-concept experiments to validate assumptions and key performance indicators. - Collaborate with teams and stakeholders to refine requirements, interpret results, and deliver actionable insights