Applied AI Associate (Public Health), Health Analytics and AI Unit - Digital Health
Join as an Applied AI Associate to drive health analytics and AI solutions in public health.
Overview
Join as an Applied AI Associate to drive health analytics and AI solutions in public health.
You have:
- Bachelor's or master's degree in computer science, data science, statistics, public health, or a closely related field.
- Minimum 5 years of experience in building ML/AI systems, taking them from prototype to production and maintaining them in live production.
- Hands-on experience evaluating and benchmarking LLM-based systems.
- Experience building retrieval-augmented generation (RAG) systems.
- Experience with anonymisation and de-identification pipelines.
- Comfort with large-scale data processing and query optimisation over large data.
- Understanding of the public-health domain, sufficient to work with programmatic data.
- Proficiency in Python and the mainstream ML stack; strong SQL.
- Fluency in English; Fluency in Hindi or an additional Indian language is an advantage.
Potential interview questions
| Describe a project where you successfully implemented an ML system in a public health context. | This assesses your experience in relevant fields and how you apply your skills in real scenarios. | Provide specific details about your role, the challenges faced, and the outcomes. |
| How do you ensure the quality and accuracy of AI models in production? | The interviewer wants to know your approach to maintaining the integrity of models. | Pro members can see the explanation. |
| Can you explain a time you worked with stakeholders to translate project goals into technical requirements? | Pro members can see the explanation. | Pro members can see the explanation. |
| What experience do you have with data anonymisation and how does it relate to public health? | Pro members can see the explanation. | Pro members can see the explanation. |
| Discuss a challenge you faced while working with large datasets and how you overcame it. | Pro members can see the explanation. | Pro members can see the explanation. |
| How would you address issues related to bias and fairness in AI models? | Pro members can see the explanation. | Pro members can see the explanation. |
| Describe your experience with implementing natural language processing in your projects. | Pro members can see the explanation. | Pro members can see the explanation. |
| What strategies do you use to stay updated with trends in AI and public health? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 1 month ago
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Updated 3 days ago
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Source:
clintonhealthaccess.org
