Requirements
1. Bachelor's degree or higher in Computer Science, Data Science, Business Analytics or a related field, with at least 3+ years of relevant professional experience.
2. Core Data Science & ML skillset
- Strong foundation in machine learning, with hands-on experience in model development and experimentation.
- Strong programming proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Ability to analyze model behavior, diagnose training issues, and design experiments to improve performance.
3. Applied Research & Experimentation
- Familiarity with reading, synthesizing, and ability to translate emerging research into practical prototypes.
4. Software Engineering
- Working knowledge of backend development (REST APIs, FastAPI, Flask, or similar).
- Comfortable working with cloud environments (AWS preferred).
- Ability to debug and fix software-level issues when they affect ML workflows.
- Familiarity with Git, CI/CD, and collaborative coding best practices.
5. Nice-to-Haves
- Experience with privacy-enhancing technologies, anonymization, synthetic data generation or differential privacy.
- Familiarity with frontend integration workflows (Next.js/React).
- Prior experience working in multi-disciplinary product teams.
6. Mindset & Collaboration
- Curiosity and willingness to learn new domains (esp. data privacy).
- Strong communication skills to explain technical concepts to both engineers and non-technical stakeholders.
- Inclination to work in a collaborative, fast-moving Agile environment
