Data Scientist

1. Optimization Problem-Solving:

• Develop and implement mathematical models/ Genetic Computational Models/ Reinforcement Algorithms for space optimization problems.
• Apply optimization techniques to maximise space utilisation while adhering to specific constraints (e.g., weight, dimension, arrangement rules).

2. Constraint Management:

• Identify and incorporate constraints such as safety standards, weight distribution, and accessibility into optimization solutions.
• Design solutions to minimise risks (e.g., damage, inefficiencies) while adhering to constraints.

3. Mathematical Modelling:

• Use advanced mathematical techniques to design, test, and refine optimization algorithms.
• Analyse problem statements and propose efficient, scalable solutions.

4. Data-Driven Insights:

• Analyse spatial data to identify optimization opportunities.
• Generate meaningful insights from simulations and real-world tests.

5. Collaboration and Reporting:

• Collaborate with cross-functional teams to gather requirements and deliver optimised layouts and plans.
• Prepare clear and concise reports or visualisations to communicate results and methodologies to stakeholders.

Qualifications and Skills Required:

• Bachelor s degree in Computer Science, or a related field.
• Strong understanding of optimization techniques such as heuristic algorithms, Genetic Algorithms, or Reinforcement Algorithms.
• Proficiency in mathematical tools Python.
• Solid grasp of spatial reasoning and geometric principles.
• Ability to solve complex problems using structured and logical approaches.

Preferred:

• Basic knowledge of data science concepts such as data preprocessing, statistical analysis., Machine Learning Algorithms, Deep-learning, Reinforcement Learning
• Experience with tools like Pandas, NumPy, scikit-learn, or TensorFlow.
• Familiarity with container packing, or related optimization scenarios.
• Strong communication skills to articulate technical solutions to non-technical stakeholders.