Senior ML/AI Researcher II - ML and AI modeling
Remote, United States
Aledade
Aledade works with independent practices, health centers, and clinics to build and lead Accountable Care Organizations (ACOs) anchored in primary care.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:
- 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.
Minimum Qualifications:
- BA/BTech in Statistics, Data Science, Computer Science or a related field require.
- 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 of 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.
- Background in Epidemiology, particularly in the context of chronic condition modeling.
- 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.
- 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Causal inference Computer Science Deep Learning Distributed Systems Economics EMNLP Engineering Feature engineering ICML LLMs Machine Learning Mathematics NeurIPS PhD Physics Python R Research SAS Security Spark Statistics
Perks/benefits: Conferences
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