Improving healthcare data latency through automation by building scalable, production-ready machine learning and statistical models
Requirements
- Experience working in a heavily regulated industry. Healthcare is a plus
- Advanced course in machine learning and programming
- Experience with building, delivering and maintaining production ready machine learning models
- Knowledge of statistical data analysis and machine learning such as linear models, time series forecasting, neural network, random forest and NLP models, etc
- Expert in Python coding and utilization of machine learning and statistical packages for modeling
- Experience With Database Skills, SQL, NoSQL, Coding For ETL
- Familiarity with Spark, Azure, Databricks, MLFlow AutoML
Responsibilities
- Designs, develops and delivers statistical and/or machine learning models that solve business problems and work with engineers to make them production ready
- Develops, utilize and monitor end-to-end machine learning pipeline from data ETL to model delivery for product ionization
- Leads rapid prototyping for new business problems to support feasibility analysis for AI products
- Builds and adopts solutions to automate and integrate data science processes
- Researches latest and best solutions to solve data challenges at hand
- Interprets and communicates results of complex models with cross functional team and the stakeholders
- Generate internal implementations to achieve results
Other
- Bachelor's Degree in a quantitative/statistical or business field (e.g., Statistics, Mathematics, Engineering, Computer Science)
- 6 years of related experience or equivalent experience acquired through accomplishments of applicable knowledge, duties, scope and skill reflective of the level of this position
- Excellent verbal and written communication skills, communicate complex findings in a clear and understandable manner
- Ability to work independently
- Demonstrated analytical skills
