Senior Data Scientist / Machine Learning Engineer

Terumo Medical Corporation - Franklin Township, NJ

Full-time - Mid Level

Franklin Township, NJ

10,001+ employees

Merchant Wholesalers, Durable Goods

About the position

The Sr. Data Scientist, Machine Learning Engineer position at Terumo Americas Holding, Inc. is a pivotal role that leverages cloud computing technologies to develop, deploy, and manage predictive models that support decision-making processes across the organization. This position is integral to the Terumo Medical Corporation's mission of advancing healthcare with heart by providing impactful solutions for patients. The role involves a comprehensive approach to data science, including the collection, cleaning, and preprocessing of large datasets to prepare them for analysis. The successful candidate will design and build predictive models using various machine learning algorithms, ensuring that these models are effectively deployed in a cloud environment. In this role, the Data Scientist will continuously monitor model performance, making necessary adjustments to enhance accuracy and efficiency. This includes implementing A/B testing and other validation techniques to ensure the reliability of the models. Collaboration is key, as the Data Scientist will work closely with data engineers, cloud architects, and business analysts to integrate predictive models into business processes, providing insights and recommendations based on model outputs. Documentation and reporting are also critical components of the job, requiring the candidate to document the modeling process and prepare reports and visualizations to communicate findings to non-technical stakeholders. The position is designed for individuals who are not only technically proficient but also possess strong analytical and problem-solving skills. The ideal candidate will have experience with big data technologies, familiarity with DevOps practices, and a solid understanding of data architecture principles. Terumo values personal growth and encourages employees to deepen their skills throughout their careers, fostering an environment where innovation and collaboration thrive.

Responsibilities

• Collect, clean, and preprocess large datasets to prepare them for analysis.
• Identify patterns, outliers, and trends within the data.
• Design and build predictive models using machine learning algorithms.
• Experiment with various algorithms and tuning parameters to optimize model performance.
• Deploy models in a cloud environment, ensuring they are scalable, reliable, and secure.
• Utilize cloud services (e.g., AWS, Azure, Google Cloud) for computing resources, data storage, and model hosting.
• Continuously monitor model performance, making adjustments as needed to improve accuracy and efficiency.
• Implement A/B testing and other techniques to validate models.
• Work closely with data engineers, cloud architects, and business analysts to integrate predictive models into business processes.
• Provide insights and recommendations based on model outputs.
• Document the modeling process, including data sources, model choices, and parameter configurations.
• Prepare reports and visualizations to communicate findings to non-technical stakeholders.
• Perform other job-related duties as required.

Requirements

• Bachelor's in Computer Science, Data Science, Statistics, or equivalent work experience.
• Minimum 5 years' experience in data science, with experience in predictive modeling and unsupervised machine learning.
• Experience in programming languages (such as Python or C#) and familiarity with SQL required.
• Experience deploying data/code to cloud computing platforms (such as AWS, Azure, Google Cloud) and their data analytics services preferred.
• Experience with big data technologies (Hadoop, Spark) and understanding of data architecture principles.
• Familiarity with DevOps practices for data science, including CI/CD pipelines for model deployment.
• Excellent analytical and problem-solving skills and ability to work with large, complex data sets.
• Outstanding written and verbal presentation skills.
• Experience with forecasting methodologies and ability to work with limited information to create forecasts.
• Advanced proficiency with data mining, mathematics, and statistical analysis.
• Advanced pattern recognition and predictive modeling experience.
• Knowledge of machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Experience with agile methodology.
• Must be able to work independently with minimal direction.
• Must exhibit strong teamwork and be adept at working cross-functionally.

Nice-to-haves

• Certifications in cloud computing platforms and machine learning are a plus.