AI Data Scientist

When you join the growing BILH team, you're not just taking a job, you’re making a difference in people’s lives.

The AI Data Scientist role is designed for individuals who are interested in applying data science, machine learning, and generative AI to healthcare and operational challenges.

This position emphasizes fundamental understanding of generative AI and large language models (LLMs), including how models are trained, finetuned, evaluated, and applied responsibly. The role focuses on model development, experimentation, evaluation, and analytical reasoning.

The AI Data Scientist will work as part of a multidisciplinary team and receive mentorship while developing skills across the AI and data science lifecycle, from data exploration and modeling to evaluation and communication of results.

Job Description:

 Essential Duties & Responsibilities including but not limited to:

1. Support the development and evaluation of machine learning and generative AI models for healthcare analytics, automation, and decision support.  

2. Build a foundational understanding of large and small language models (LLMs), including basic architecture concepts, embeddings, inference behavior, and limitations.  

3. Assist with prompt design, prompt testing, and prompt optimization to improve accuracy, relevance, and consistency of LLM outputs.  

4. Participate in LLM finetuning activities (such as instruction tuning or parameter efficient finetuning) under guidance and within established workflows.  

5. Help design and execute model evaluation approaches, including quantitative metrics and qualitative review of LLM outputs (accuracy, completeness, bias, hallucinations).  

6. Contribute to retrieval of augmented generation (RAG) projects by assisting with data preparation, document evaluation, and grounding assessments.  

7. Perform exploratory data analysis, data validation, and feature engineering for predictive and descriptive modeling tasks.  

8. Collaborate with senior data scientists, data engineers, clinicians, and business stakeholders to translate problems into data science and AI modeling work.  

9. Create visualizations, written summaries, and presentations to communicate insights and model performance to technical and nontechnical audiences.  

10. Follow Responsible AI practices, including awareness of fairness, bias, privacy, transparency, and appropriate AI use in healthcare.  

11. Participate in team meetings, mentoring sessions, and ongoing learning activities related to AI and data science.

Minimum Qualifications:

Education: 

Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, or a related quantitative field required.  

Relevant coursework or academic projects in machine learning, NLP, or AI strongly preferred. 

Licensure, Certification & Registration:<