Data Scientist

Responsibilities

• Design and implement advanced optimization algorithms for deployment in real-time systems within TracOS.
• Develop and apply methods such as linear programming, simplex, branch and bound, gradient descent, and other optimization techniques.
• Work closely with engineering and data teams to integrate optimization models into production, ensuring smooth operation and high reliability.
• Monitor algorithm performance continuously and adjust models to enhance effectiveness and accuracy.
• Collaborate with product teams to identify client needs and customize optimization solutions accordingly.
• Document optimization processes and models, providing guidelines and insights for future improvements and scaling.

Requirements

• Proven experience implementing optimization algorithms in production settings, with a preference for industrial or asset management applications.
• Strong expertise in linear programming, including the application of simplex and other optimization methods.
• Solid knowledge of gradient descent, branch and bound, and other algorithmic optimization techniques.
• Proficiency in Python, with hands-on experience in libraries such as SciPy, NumPy, or similar tools for optimization.
• Familiarity with maintenance planning processes and predictive maintenance principles is highly desirable.
• Strong analytical skills, attention to detail, and an ability to work both independently and collaboratively in a fast-paced environment.