Junior Data Scientist

We're seeking a Junior Data Scientist to join our client's team and contribute to data-driven decision-making through optimization techniques and code development. This role requires a strong foundation in Python (particularly with Pyomo and Ipopt) and SQL, with an emphasis on optimization problem-solving. The ideal candidate will be analytical, technically skilled, and comfortable with coding in a production environment.

Key Responsibilities:

Optimization & Analysis: Apply optimization techniques to model objective functions, constraints, and feasibility in various scenarios.

Data Understanding: Analyze input and output data to diagnose issues, identify infeasibilities, and make data-driven recommendations.

Code Development: Enhance and maintain Python code, including adjustments to constraint bounds and refining optimization models.

Experimentation: Conduct small-scale experiments on constraint bounds to improve model accuracy and efficiency.

Production Environment Coding: Write efficient, scalable code for deployment in a production environment, ensuring robust performance.

Version Control: Use Git for version control to track changes, collaborate with team members, and manage code repositories.

Requirements:

Technical Skills:

• Proficiency in Python, with experience using Pyomo and Ipopt for optimization tasks.
• Strong SQL skills for data querying, manipulation, and analysis.
• Understanding of optimization concepts such as objective functions, constraints, feasibility, and bounds.
  
  
  

Experience:

• Prior experience working in a production environment, including deployment and maintenance of code.
• Familiarity with version control systems, specifically Git, for collaborative code management.
  
  
  

Analytical Skills:

• Ability to make sense of complex data and identify root causes of infeasibility in optimization models.
• Strong problem-solving skills with attention to detail in interpreting and analyzing data inputs and outputs.
  
  
  

Preferred Qualifications:

• Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
• Experience conducting experiments to enhance and improve optimization models.
• Familiarity with other libraries or tools related to optimization and data science.