Senior Data Scientist - Remote | Trading Analytics & ML Models

We're seeking an experienced Data Scientist to join our innovative trading analytics team on a permanent, full-time remote basis. You'll leverage machine learning expertise and Python proficiency to develop predictive models that optimize trading strategies and enhance client behavior analysis. This role offers exceptional growth opportunities for professionals passionate about transforming complex data into actionable trading insights. Key Responsibilities: - Collaborate with Business departments to understand current requirements and assess how product changes impact existing machine learning solutions. - Enhance performance of current ML models through algorithmic optimization and innovative approaches. - Develop sophisticated predictive models for user behavior analysis, including churn prediction, conversion optimization, and lifetime value (LTV) forecasting. - Productionalize machine learning models with end-to-end implementation - from data preprocessing and feature engineering to deployment and monitoring. - Conduct comprehensive exploratory data analysis (EDA) of client behavioral data using Python, SQL, and PySpark frameworks. - Improve internal codebase quality through systematic refactoring and development of automated tools for ML model lifecycle management. - Translate complex analytical findings into accessible insights for non-technical business stakeholders. - Implement continuous improvement initiatives to enhance data pipeline efficiency and model accuracy metrics. Required Skills & Qualifications: - 1-3 years of professional experience developing and implementing machine learning solutions in production environments. - Upper-Intermediate to Advanced English proficiency (both written and verbal communication). - Strong programming skills in Python (Python 3.10+) with proficiency in data science libraries (NumPy, Pandas, Scikit-learn). - Practical experience with SQL for complex data extraction and analysis. - Proficient with Git version control for collaborative development workflows. - Solid understanding of machine learning concepts, including supervised and unsupervised learning techniques. - Experience with data visualization tools and libraries (Matplotlib, Seaborn, Plotly, or similar). - Ability to work independently while maintaining clear communication with cross-functional teams. - Problem-solving mindset with strong analytical capabilities in a fast-paced environment. Nice to Have: - Experience with deep learning frameworks, particularly PyTorch 2.0+. - Knowledge of PySpark for large-scale distributed data processing. - Familiarity with Docker containerization for creating reproducible development environments. - Understanding of cloud computing concepts and experience with AWS services (SageMaker, S3, EC2, Lambda). - Prior experience developing client scoring models and implementing predictive metrics in financial decision-making processes. - Successful participation in Kaggle competitions demonstrating practical ML implementation skills. - Background in trading, fintech, or financial services industries. - Experience analyzing complex client behavior patterns and business performance metrics. - Knowledge of A/B testing methodologies for model evaluation and optimization. - Experience with ML model monitoring and maintenance in high-stakes production environments. Why Join Our Team: Work with cutting-edge technologies in a dynamic trading environment where your models directly impact business outcomes. Enjoy the flexibility of remote work with a collaborative team focused on innovation. We offer competitive compensation, professional development opportunities, and the chance to solve complex data challenges using the latest machine learning techniques. Join us to build predictive solutions that transform trading strategies and business decisions through data science excellence.