Job Description
Overview
Build and maintain VNS's internal Data Science (DS) and Machine Learning (ML) platforms, enabling VNS Data Scientists to deliver data insights to operational and clinical stakeholders more efficiently. Support Data Science automation by building and maintaining CI/CD pipelines, MLOps model deployment pipelines, and other pipelines triggered by events across the Data Science lifecycle. Develop and sustain production tools and services, including data-intensive web applications, dashboards, and ML services. Contribute to implementing and maintaining Analytics-as-a-Service products offered through the VNS Health Management Services Organization (MSO). Operate under general supervision.Compensation Range:$98,200.00 - $130,800.00 AnnualWhat We Provide
- Referral bonus opportunities
- Generous paid time off (PTO), starting at 30 days of paid time off and 9 company holidays
- Health insurance plan for you and your loved ones, Medical, Dental, Vision, Life and Disability
- Employer-matched retirement saving funds
- Personal and financial wellness programs
- Pre-tax flexible spending accounts (FSAs) for healthcare and dependent care
- Generous tuition reimbursement for qualifying degrees
- Opportunities for professional growth and career advancement
- Internal mobility, generous tuition reimbursement, CEU credits, and advancement opportunities
What You Will Do
- Collaborate with clinical operations, business owners, and IT to understand VNS Health data flows and the integration of user-facing applications with database systems.
- Maintain and extend VNS BIA data transformation pipelines, primarily using dbt for orchestration on Snowflake.
- Build and maintain Docker images supporting DS/ML tools and services.
- Develop and maintain continuous integration/continuous delivery (CI/CD) pipelines using GitLab CI. JOB IS FROM: italents.netVIEW
- Leverage new cloud computing technologies (e.g., Snowflake CORTEX, new AWS services) to enhance VNS DS/ML tools and services.
- Provide support to VNS Machine Learning Engineers in maintaining ML operations (MLOps) on AWS SageMaker.
- Implement monitoring, logging, and alerting across DS/ML tools and services.
- Manage orchestration of production DS/ML workflows using Airflow.
- Contribute to developing, maintaining, and enhancing BIA DS web applications (primarily R Shiny and Python Dash applications deployed to Posit Connect).
- Participate in code reviews and support development and deployment practices based on the Software Development Life Cycle (SDLC).
- Create and maintain comprehensive documentation for data science workflows, tools, and services to facilitate knowledge sharing and onboarding of new team members.
- Ensure the accuracy of work and the validity of statistical analysis and inference.
- Solve non-routine, interdisciplinary analysis problems by applying analytical methods as needed.
- Participates in special projects and performs other duties as assigned.
Qualifications
Education:
- Bachelor's Degree in computer science, data science, or relevant work experience required
- Master's Degree in Data Science, Computer Science, or CS Engineering preferred
Work Experience:
- Minimum 2 years of industry experience in a Data Science or similar role required
- Minimum 2 years of experience using Python for both DS/ML development and as a general-purpose scripting language required
- Minimum 1 years of experience with tools such as Git, Docker, Linux command line required
- Minimum 1 years of industry experience with Snowflake (or a similar columnar cloud data warehouse) and AWS (or Azure/GCP) required
- Strong SQL skills for querying and manipulating large datasets in a cloud data warehouse environment required
- Effective oral, written and interpersonal communication skills required
- Experience with basic web technologies (HTML/CSS/JS) preferred
- Experience working with engineering and project management teams, demonstrating strong communication skills and ability to translate business requirements into software requirements preferred