Senior Data Scientist Machine Learning Engineer

<strong>Job Summary:</strong><br><br>This Senior Data Scientist, Machine Learning Engineer will leverage cloud computing technologies to develop, deploy, and manage predictive models that support decision-making processes across the Terumo organization. The role demands a strategic approach to ownership, involving collecting, cleaning, and preprocessing large datasets, designing and building predictive models using machine learning algorithms, and deploying models in a cloud environment. The Senior Data Scientist, Machine Learning Engineer will be responsible for continuously monitoring model performance and making necessary adjustments to improve accuracy and efficiency. This role includes defining and executing ownership strategies, ensuring models are integrated seamlessly into business processes, and aligning with organizational goals.<br><br><strong>Job Details:</strong><br><ol><li><strong>Data Exploration and Preprocessing:</strong></li></ol><ul><li>Collect, clean, and preprocess large datasets to prepare them for analysis.</li><li>Identify patterns, outliers, and trends within the data, ensuring high data quality and integrity.</li><li>Take ownership of the data lifecycle, from ingestion to processing, ensuring best practices and compliance.</li></ul><ol><li><strong>Model Development:</strong></li></ol><ul><li>Design and build predictive models using machine learning algorithms.</li><li>Experiment with various algorithms and tuning parameters to optimize model performance.</li><li>Lead the strategy for selecting appropriate modeling techniques and tools, ensuring alignment with business needs and technological capabilities.</li></ul><ol><li><strong>Cloud Deployment:</strong></li></ol><ul><li>Deploy models in a cloud environment, ensuring they are scalable, reliable, and secure.</li><li>Utilize cloud services (e.g., AWS, Azure, Google Cloud) for computing resources, data storage, and model hosting.</li><li>Develop and implement a comprehensive deployment strategy, emphasizing reliability, security, and scalability.</li></ul><ol><li><strong>Performance Monitoring:</strong></li></ol><ul><li>Continuously monitor model performance, making adjustments as needed to improve accuracy and efficiency.</li><li>Implement A/B testing and other techniques to validate models.</li><li>Establish and oversee a robust performance monitoring framework, ensuring proactive issue identification and resolution.</li></ul><ol><li><strong>Collaboration:</strong></li></ol><ul><li>Work closely with data engineers, cloud architects, and business analysts to integrate predictive models into business processes.</li><li>Provide insights and recommendations based on model outputs.</li><li>Champion cross-functional collaboration, driving initiatives that enhance organizational knowledge and data-driven decision-making.</li></ul><ol><li><strong>Documentation and Reporting:</strong></li></ol><ul><li>Document the modeling process, including data sources, model choices, and parameter configurations.</li><li>Prepare reports and visualizations to communicate findings to non-technical stakeholders.</li><li>Lead efforts to maintain comprehensive and transparent documentation, facilitating knowledge sharing and continuous improvement.</li></ul><ol><li><strong>Leadership and Strategic Initiatives:</strong></li></ol><ul><li>Define and execute the ownership strategy for machine learning initiatives, ensuring alignment with Terumo's overall business strategy.</li><li>Mentor and guide junior data scientists and team members, fostering a culture of excellence and continuous learning.</li><li>Proactively identify and drive strategic initiatives that leverage data science to create competitive advantages for Terumo.</li></ul><br><strong>Position Requirements:</strong><br><br><strong>Knowledge, Skills and Abilities (KSAs)</strong><br><br>Experience with big data technologies (Databricks) and understanding of data design patterns (medallion architecture).<br><br>Familiarity with DevOps practices for data science, including CI/CD pipelines for model deployment.<br><br>Certifications in cloud computing platforms and machine learning are a plus.<br><br>Excellent analytical and problem-solving skills and ability to work with large, complex data sets.<br><br>Outstanding written and verbal presentation skills to effectively communicate complex concepts to a variety of stakeholders.<br><br>Experience with forecasting methodologies and ability to work with limited information to create forecasts.<br><br>Advanced proficiency with data mining, mathematics, and statistical analysis.<br><br>Advanced pattern recognition and predictive modeling experience.<br><br>Knowledge of machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and data visualization tools (e.g., Matplotlib, Seaborn, Tableau).<br><br>Experience with agile methodology, working closely with the SCRUM master to plan sprints, run retrospectives, participate in standups, and other planning meetings.<br><br>Independent work capability, with minimal direction required.<br><br>Strong teamwork skills, adept at working cross-functionally.<br><br><strong>Background Experiences</strong><br><br>Bachelor's/Master's in Computer Science, Data Science, Statistics, or equivalent work experience.<br><br>Minimum 7 years' experience in data science, with experience in predictive modeling and unsupervised machine learning. <br><br>Experience in programming languages (such as Python or C#) and familiarity with SQL required<br><br>Experience deploying data/code to cloud computing platforms (such as AWS, Azure, Google Cloud) and their data analytics services preferred.