As a Senior AI Researcher II, you will develop ML and AI solutions that will improve health for millions of people. At Aledade, we empower primary care physicians with technology to keep their patients healthy and prevent unnecessary hospitalizations. You will collaborate with engineering and analytics teams to integrate AI technology into existing products and workflows.

You will work with one of the most extensive data sets of medical records, diagnoses, claims, and prescriptions. This role offers a unique opportunity to train, fine-tune, and use AI models using medical data collected from millions of patients across the country.

Primary Duties:

• Build ML/AI models to identify patients who will benefit most from interventions, supporting value-based care strategies.
• Collaborate with engineering, analytics, and product teams to integrate AI into existing healthcare products.
• Analyze large datasets to extract insights that improve patient outcomes and guide clinical decisions.
• Deliver AI-driven Proof of Concepts (POCs), focusing on speed, scalability, and efficiency.
• Ensure fairness and transparency in all models, promoting ethical AI use.
• Stay updated on AI/ML advancements and apply them to healthcare innovations.

Minimum Qualifications:

• BA/BTech in Statistics, Data Science, Computer Science or a related field required.
• 6+ years of relevant statistical analysis experience.
• 6+ years of relevant machine learning experience (ML modeling, hyperparameter tuning, feature engineering, model validation etc)
• Understanding of causal inference and treatment effects estimation. 
• 3-5 years of experience selecting, implementing, and optimizing ML tools and frameworks for large-scale projects.
• 2+ years or Python language experience.
• 1+ years of relevant deep learning and LLM experience.
• 1+ 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.
• Contributions to the field (e.g., publications, patents, or successful large-scale implementations).

Preferred KSA's:

• Master or PhD 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 health-tech systems, like Electronic Health Records, Clinical data, etc.
• 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. 
• Publications at peer-reviewed conferences (e.g. NeurIPS, ICML, ACL, JSM, KDD, EMNLP).
• Participation in ACIC Data Challenge, Kaggle etc.

Physical Requirements:

• Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.