Junior ML Analyst

Junior ML Analyst (STEM OPT)

1. Model Development & Experimentation

Algorithm Implementation: Apply advanced theoretical knowledge from CSCE 5215 (Machine Learning) to select, implement, and train supervised and unsupervised learning models.

Hyperparameter Tuning: Use Empirical Analysis (CSCE 5310) to perform systematic grid searches and Bayesian optimization, improving model metrics such as F1-score and Mean Squared Error.

Prototyping Agentic Systems: Research and develop autonomous agent workflows that leverage Large Language Models (LLMs) to automate complex business requirements gathered from stakeholders.

2. Data Engineering & Feature Analysis

Pipeline Construction: Design and maintain robust data pipelines using Python and SQL, ensuring data integrity for high-volume training sets as mastered in CSCE 5350 (Fundamentals of DB).

Feature Engineering: Perform exploratory data analysis (EDA) on Big Data (CSCE 5300) to identify key variables, handle missing data, and perform dimensionality reduction to enhance model performance.

Data Modeling & Transformation: Utilize INFO 5707 (Data Modeling) principles to structure non-relational and relational data for efficient ingestion into ML frameworks like PyTorch or Scikit-learn.

3. Deployment & MLOps Support

Full-Stack Integration: Collaborate with the engineering team to integrate ML models into web applications using Vite and React, ensuring low-latency inference for end-users.

Secure AI Deployment: Work with the security team to implement Secure E-Commerce (CSCE 5560) protocols for AI-driven transaction monitoring and fraud detection systems.

Model Monitoring: Build dashboards to track model drift and performance over time, ensuring that production models maintain their accuracy against evolving datasets.

4. Technical Research & Documentation

STEM OPT Milestone Tracking: Maintain comprehensive technical logs and training documentation as required by the Form I-983, bridging academic concepts with industrial application.

Cross-Functional Translation: Translate complex algorithmic results into actionable business insights for non-technical leadership at Navonsys.

Algorithm Auditing: Conduct regular code reviews and audits for computational efficiency, applying principles from CSCE 5150 (Computer Algorithms).

Key Technical Competencies

Programming: Python (Pandas, NumPy, Scikit-learn), SQL, TypeScript.

Frameworks: Vite, React, Hono (for lightweight ML APIs).

Environment: Docker for containerized model deployment, Git for version control.