Research Engineer (IORA)

Job Description

The Institute of Operations Research and Analytics (IORA) is seeking a dedicated and skilled Research Engineer to support our research projects focused on the implementation and analysis of machine learning (ML) algorithms. The successful candidate will be instrumental in providing coding expertise, data management, and analytical support to a range of projects in operations research and analytics.

This is an excellent opportunity for recent graduates passionate about applying their technical skills to real-world problems, particularly in the field of machine learning and data analytics.

Key Responsibilities

    •    Coding and Implementation: Develop and implement machine learning algorithms and models to support IORA’s ongoing and new research projects.
    •    Data Analysis: Conduct data processing, exploration, and visualization, delivering insights that guide research conclusions.
    •    Model Evaluation: Collaborate with researchers to evaluate model performance, optimizing algorithms for robustness and efficiency.
    •    Documentation: Ensure thorough documentation of code, data pipelines, and research findings to facilitate reproducibility and project continuity.
    •    Collaboration: Work closely with research teams to understand project objectives, gather requirements, and provide technical support in the form of coding and data analysis.
    •    Maintenance and Troubleshooting: Manage and troubleshoot issues in codebases and data pipelines as they arise, ensuring smooth and efficient project progress.
 

Requirements

• Education: Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, or related field.
    • Programming Skills: Proficiency in Python (preferred) or R, with experience in relevant libraries for ML and data processing (e.g., Scikit-Learn, Pandas, TensorFlow, PyTorch).
    • Data Management: Familiarity with data extraction, cleaning, and preprocessing methods; experience with SQL or other database management tools is a plus.
    • Machine Learning Knowledge: Understanding of machine learning fundamentals, including supervised and unsupervised learning, model selection, and evaluation techniques.
    • Analytical Mindset: Strong analytical and problem-solving skills with attention to detail in data analysis and algorithm implementation.
    • Team Collaboration: Ability to work collaboratively within a research environment, with effective communication skills to convey technical information clearly.

Preferred Experience

    • Experience with version control systems, such as Git.
    • Prior research experience or involvement in machine learning or data science projects is advantageous.
    • Exposure to cloud computing platforms like AWS or GCP for ML model deployment (optional but a plus).

How to Apply
Interested applicants should submit their resume, a cover letter detailing their interest in the role, and any relevant project portfolios or coding samples that demonstrate their experience with ML and data analysis.