Staff AI Researcher

Summary

Join Aledade as a Staff AI Researcher and develop ML and AI solutions to improve healthcare for millions. Partner with engineering and analytics teams to integrate AI into existing products and workflows. Lead the effort to leverage a vast dataset of medical records to train, fine-tune, and utilize AI models. This role offers a unique opportunity to contribute to advancements in AI within the healthcare industry. You will be responsible for training and fine-tuning models, working with large datasets, and delivering working solutions. The position requires a strong background in statistics, data science, and machine learning.

Requirements

• BA/BTech in Statistics, Data Science, Computer Science or a related field required
• 8+ years of relevant statistical analysis experience
• 8+ years of relevant machine learning experience (ML modeling, hyperparameter tuning, feature engineering, model validation etc
• Background in Epidemiology, particularly in the context of chronic condition modeling
• 5-7 years of experience selecting, implementing, and optimizing ML tools and frameworks for large-scale projects
• 3+ years of Python language experience
• 2+ years of relevant deep learning and LLM experience
• 2+ years experience working with large-scale distributed systems at scale and statistical software (e.g. Spark)
• Experience in addressing challenges from incomplete, unrepresentative, and mislabeled data
• Track record of significant contributions to the field (e.g., publications, patents, or successful large-scale implementations)

Responsibilities

• Train and fine-tune models using off-the-shelf and novel ML/AI techniques solving optimization problems for the company
• Work with large, complex data sets. Conducting difficult, non-routine analysis and harvesting data
• Deliver working POC solutions solving speed, scalability and time-to-market tradeoffs

Preferred Qualifications

• Ph.D. or Master's degree in a quantitative discipline (e.g., Computer Science[with AI/ML Major], Statistics, Operations Research, Economics, Mathematics, Physics) or equivalent practical experience
• Working knowledge of Public Health, with a focus on Value-Based Care and Risk adjustment
• Working knowledge of health-tech systems, such as Electronic Health Records and clinical data
• Proficiency in communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training
• Experience with security and systems that handle sensitive data
• Experience working with statistical software (e.g. R, SAS, Python statistical packages)
• Demonstrated leadership and self-direction
• First-author publications at peer-reviewed conferences (e.g. NeurIPS, ICML, ACL, JSM, KDD, EMNLP)
• Winners in ACIC Data Challenge, Kaggle etc