Senior Data Scientist

Are you passionate about using data to drive operational efficiency and reliability?

We're looking for a Data Scientist to join our client's team and spearhead the development of predictive maintenance models for our train fleet and other critical assets. You’ll be at the forefront of leveraging data to predict equipment failures, optimize resources, and ensure the safety and efficiency of our operations.

Key Responsibilities:

• Collaborate with Stakeholders (e.g., Rapid Rail, Rapid Bus) to understand asset health, maintenance, and business goals.
• Design & Implement Data Pipelines for collecting data from various sources, including building management systems and sensor data.
• Develop Predictive Maintenance Models to forecast equipment failures, estimate remaining useful life (RUL), and optimize maintenance schedules.
• Use Machine Learning Algorithms (e.g., anomaly detection, time series forecasting) to predict and prevent breakdowns.
• Work with Data Engineers to ensure data integrity and collaboration with cross-functional teams for smooth model integration.
• Continuously Monitor & Refine Models for optimal performance, expanding predictive insights to other equipment as opportunities arise.
• Communicate Data Insights through actionable reports to the technical and asset management teams.
• Stay updated on the latest advancements in predictive maintenance and data science trends.

Qualifications:

• 8+ years of experience as a Data Scientist or in a similar role, with a proven track record of predictive modeling.
• Master’s degree in Statistics, Computer Science, Mathematics, or a related field (or equivalent experience).
• Proficiency in Python, R, SQL, and machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Expertise in Machine Learning Algorithms like survival analysis, time series forecasting, and anomaly detection.
• Strong analytical and problem-solving skills focused on data-driven maintenance optimization.
• Excellent Communication Skills to translate complex data insights into actionable recommendations for both technical and non-technical audiences.
• A collaborative mindset, with the ability to work across diverse teams and manage multiple projects.