Data Scientist

Job Title: Mathematical Modeler / Data Scientist (Smart Cranes Alarming Engine, Offsite)

Role Overview:

We are seeking a Mathematical Modeler / Data Scientist to support the development of a state-of-the-art alarming engine for our Smart Cranes system. This offsite role requires expertise in mathematical modeling, machine learning, and predictive analytics to drive operational efficiency and safety through real-time anomaly detection and predictive maintenance.

Key Responsibilities:

• Model Development: Design and implement advanced mathematical models to power the alarming engine, enabling real-time anomaly detection and failure predictions for Smart Cranes.
• Data Analysis: Perform data exploration, preprocessing, and feature engineering on sensor data and operational logs to identify key patterns and failure indicators.
• Machine Learning: Build, train, and optimize machine learning models to predict failures, enhance equipment performance, and trigger automated alarms.
• Alarming Logic: Develop logic-based rules and integrate them with machine learning models to create effective alarming mechanisms for operators.
• Collaboration: Work closely with cross-functional teams, including engineers and domain experts, to validate models and improve predictive accuracy.
• Model Validation: Continuously evaluate model performance using real-world data, refining models for higher precision and reliability.
• Data Visualization: Develop dashboards and visualizations to present model outcomes and system states to stakeholders in an accessible manner.
• Documentation: Maintain detailed documentation of methodologies, algorithms, and results, presenting insights to technical and non-technical teams.

Qualifications:

• Experience: 5+ years in data science, mathematical modeling, or machine learning, ideally within industrial IoT or predictive maintenance domains.
• Technical Expertise:
• Strong proficiency in programming languages like Python, R, or MATLAB.
• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Expertise in statistical analysis, optimization techniques, and time-series analysis.
• Familiarity with signal processing, sensor data, and anomaly detection.
• Collaboration: Excellent communication and teamwork skills to work effectively in a remote, multi-disciplinary environment.
• Education: Bachelor’s or Master’s degree in Mathematics, Statistics, Data Science, or a related field. PhD is a plus.