Machine Learning Engineer II

Job Description

• Develop, train, and fine-tune machine learning models using healthcare data, leveraging strong engineering instincts and debugging skills. • Conduct thorough data exploration, validation, and discovery to identify opportunities for model improvement. • Establish and monitor key performance metrics to ensure model accuracy and effectiveness. • Analyze data to generate actionable insights, translating complex findings into clear, impactful narratives. • Anticipate needs, think on your feet, and tackle tasks hands-on to find effective solutions. • Effectively articulate insights and ideas to both technical and non-technical stakeholders, showcasing the impact and value of models. • Advocate for and implement best practices in machine learning methodologies within the team and organization. • Stay current with industry trends, continuously enhancing your skills and adapting to shifting priorities. • Work independently with minimal supervision while also contributing positively to a collaborative team environment. • Demonstrate determination and perseverance in overcoming obstacles and driving projects to successful completion.

Qualifications

• Bachelor’s Degree in STEM (Master’s Preferred) • Strong foundation in core machine learning techniques and methodologies. • Proficiency in data analytics and performance metrics development. • Excellent communication skills for translating technical details into business impacts. • Ability to work independently and proactively identify opportunities for improvement. • Proficiency in AWS (SageMaker strongly preferred) • Strong programming skills in Python for developing machine learning models. • Proficiency in SQL, preferably Postgres, for data manipulation and querying. • Solid understanding of statistical principles and their application in building machine learning models. • Knowledge of probability and its impact on model development and performance.

Benefits

• 11 paid holidays • Generous Accrued Time Off increasing with years of service • Generous paid sick time • Annual day of service