Machine Learning Engineer
TapestryHealth
RemoteRemote$120,000 - $130,000 a year
Job Description
POSITION SUMMARY:
TapestryHealth is seeking outstanding candidates with strong predictive analytics, machine learning, natural language processing, python automation, and data visualization, experience. Success in this role requires dedication to excellence in helping TapestryHealth to deliver high-quality care and promote broad adoption of our technology with streamlined, data-informed processes.
We are looking for a Machine Learning Engineer to analyze large data sets to inform
improvements in our services and operations using advanced Machine Learning, Large
Language Models, AI, and other advanced methods. We will rely on you to build tools and products to extract valuable business insights for both internal users and client users.
In this role, you should be highly analytical with a knack for deriving actionable insights
from data and making business processes more efficient. Critical thinking, problem-solving, cross-functional collaboration, and clear communication skills are essential for success in this role.
We also want to see experience with healthcare data and research. Your goal will be to help our company deliver high quality care services with a more efficient and data informed approach.
PRIMARY RESPONSIBILITIES:
Design, develop, and put in production machine learning (ML) solutions
Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning.
Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
Participate in code reviews, testing, and quality assurance processes.
Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services.
Implement system telemetry, A/B testing and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
Document and communicate development processes, system designs, and architectural decisions.
Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.
REQUIREMENTS
Masters degree in Statistics, Computer Science, or relevant quantitative field
2 or more years of experience in healthcare domain
Proven experience as a Data Scientist / Machine learning engineer in delivering high quality data analyses and implementing high quality predictive analytics in production environments
Proficiency in using scripting languages such as R, SQL or Python
Proficiency in using big data analytics tools such as SPARK
Experience with data engineering orchestration tools such as Prefect, or Airflow
Ability to own the entire machine learning life cycle from design, training, deployment, and monitoring
Proficient with MLOPS tools such as MLFlow, Kedro
Adheres to software engineering best practices such as source code version control (GIT), data version control (DVC), and writes clean modular code
Strong math skills (statistics & linear algebra)
Problem-solving aptitude
Excellent communication and presentation skills
PREFERRED SKILLS
Experience in working with team members to promote ideas, issues, and initiatives within a constructive group framework
Must always represent the organization in a positive and professional manner
Ability to organize and prioritize tasks
Ability to work independently, be attentive to detail and maintain a positive attitude.
TapestryHealth is seeking outstanding candidates with strong predictive analytics, machine learning, natural language processing, python automation, and data visualization, experience. Success in this role requires dedication to excellence in helping TapestryHealth to deliver high-quality care and promote broad adoption of our technology with streamlined, data-informed processes.
We are looking for a Machine Learning Engineer to analyze large data sets to inform
improvements in our services and operations using advanced Machine Learning, Large
Language Models, AI, and other advanced methods. We will rely on you to build tools and products to extract valuable business insights for both internal users and client users.
In this role, you should be highly analytical with a knack for deriving actionable insights
from data and making business processes more efficient. Critical thinking, problem-solving, cross-functional collaboration, and clear communication skills are essential for success in this role.
We also want to see experience with healthcare data and research. Your goal will be to help our company deliver high quality care services with a more efficient and data informed approach.
PRIMARY RESPONSIBILITIES:
Design, develop, and put in production machine learning (ML) solutions
Collaborate with product managers, engineers, and other stakeholders as a specialist and subject matter expert in machine learning.
Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment.
Participate in code reviews, testing, and quality assurance processes.
Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services.
Implement system telemetry, A/B testing and other statistical methods to validate the effectiveness of AI models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes.
Document and communicate development processes, system designs, and architectural decisions.
Ensure the security and compliance of healthcare data, adhering to HIPAA regulations.
REQUIREMENTS
Masters degree in Statistics, Computer Science, or relevant quantitative field
2 or more years of experience in healthcare domain
Proven experience as a Data Scientist / Machine learning engineer in delivering high quality data analyses and implementing high quality predictive analytics in production environments
Proficiency in using scripting languages such as R, SQL or Python
Proficiency in using big data analytics tools such as SPARK
Experience with data engineering orchestration tools such as Prefect, or Airflow
Ability to own the entire machine learning life cycle from design, training, deployment, and monitoring
Proficient with MLOPS tools such as MLFlow, Kedro
Adheres to software engineering best practices such as source code version control (GIT), data version control (DVC), and writes clean modular code
Strong math skills (statistics & linear algebra)
Problem-solving aptitude
Excellent communication and presentation skills
PREFERRED SKILLS
Experience in working with team members to promote ideas, issues, and initiatives within a constructive group framework
Must always represent the organization in a positive and professional manner
Ability to organize and prioritize tasks
Ability to work independently, be attentive to detail and maintain a positive attitude.