Senior Data Scientist

As an experienced Data Scientist, your role will involve the following responsibilities: - Lead the development of predictive models from exploration to full-scale production deployment, taking ownership of the entire product lifecycle. - Build robust regression, time-series, and deep learning models to predict prices/values of financial assets, oil, apparel, and other commodities. - Continuously monitor and fine-tune models for accuracy, performance, and scalability using real-time data feedback for model optimization. - Collaborate with engineering teams to ensure successful deployment and monitoring of models in production environments as part of ML Ops & Deployment. - Work closely with product, strategy, and business teams to translate business problems into analytical frameworks, fostering effective Stakeholder Collaboration. - Define and manage pipelines and feature stores using structured and unstructured data sources to drive Data Strategy initiatives. Qualifications required for this role include: - 8+ years of experience in data science, specializing in predictive analytics and machine learning. - Demonstrated expertise in building and scaling ML models in production environments, beyond notebooks or PoCs. - Proficiency in Python, SQL, and ML libraries such as scikit-learn, XGBoost, LightGBM, TensorFlow/PyTorch. - Strong understanding of regression techniques, time-series forecasting, and feature engineering. - Preferred experience in domains like finance, commodities, retail pricing, or demand prediction. - Familiarity with cloud platforms like Azure, AWS, or GCP, as well as tools like Azure ML, Sagemaker, Airflow, Docker, and MLflow. - Ability to define success metrics, conduct A/B tests, and iterate based on measurable KPIs. - Excellent communication and storytelling skills to effectively engage both technical and non-technical stakeholders.,