Senior Ml/Ai Researcher Ii

Summary

Join Aledade as a Senior ML/AI Researcher II and develop cutting-edge AI solutions to improve healthcare for millions. Collaborate with engineering and analytics teams to integrate AI into existing products. Work with a massive dataset of medical records to train and fine-tune AI models. This role requires extensive experience in machine learning, statistical analysis, and working with large datasets. You will solve optimization problems and deliver working solutions. The ideal candidate will possess a strong academic background and contributions to the field.

Requirements

• 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 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)

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

• 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 Public Health, with a focus on Value-Based Care and Risk adjustment
• 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