JOB SUMMARY

The AI Platforms and Services (AIPS) team at Highmark Health is a critical enabler of AI-driven innovation within the company. We function as an internal service provider, delivering cutting-edge AI solutions and infrastructure to various business units and data science teams. Our mission is to empower the organization to leverage AI effectively, improve processes, and develop new AI-powered applications. The team manages the operation of enterprise AI platforms and infrastructure used by data scientist and application development teams, focuses on the development, support, best practices, policies, procedures and governance of ML models, model lifecycle management, and builds associated engineering processes designed to deploy ML and AI embedded applications efficiently and reliably in production on cloud and on prem. As a Data Scientist on the AI Platforms and Services team, your k ey responsibilities include enabling data scientists deploy models to cloud based systems, maintain machine learning and AI engineering processes (MLOps) that are deployed to cloud, building processes to monitor production AI systems, and setting up low latency and high throughput feature stores for real time scoring pipelines. Duties will include owning CI/CD application deployment pipelines for ML models, developing MLOps processes for model monitoring, model drift, evaluation of new ML tools and data science methods, and their selection and introduction to the wider organization, education and onboarding of Data Science teams to new technologies, participation in model and data code review, and horizon scanning to help maintain Highmark Health Advanced Analytics at the forefront of capability.

SKILLS

• Analysis of business problems/needs
• Analytical and Logical Reasoning/Thinking
• Collaborative Problem Solving
• Data Analysis with SQL, BigQuery
• Statistical Analysis with Python, R
• Written & Oral Presentation Skills
• Basic proto-typing/front end skills

POSITION TYPE

Office-Based
Teaches / trains others regularly
Rarely
Travel regularly from the office to various work sites or from site-to-site
Never
Works primarily out-of-the office selling products/services (sales employees)
Never
Physical work site required
No
Lifting: up to 10 pounds
Frequently
Lifting: 10 to 25 pounds
Ocassionally
Lifting: 25 to 50 pounds
Rarely
Disclaimer: The job description has been designed to indicate the general nature and essential duties and responsibilities of work performed by employees within this job title. It may not contain a comprehensive inventory of all duties, responsibilities, and qualifications required of employees to do this job.
Compliance Requirement: This position adheres to the ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies.
As a component of job responsibilities, employees may have access to covered information, cardholder data, or other confidential customer information that must be protected at all times. In connection with this, all employees must comply with both the Health Insurance Portability Accountability Act of 1996 (HIPAA) as described in the Notice of Privacy Practices and Privacy Policies and Procedures as well as all data security guidelines established within the Company’s Handbook of Privacy Policies and Practices and Information Security Policy.
Furthermore, it is every employee’s responsibility to comply with the company’s Code of Business Conduct. This includes but is not limited to adherence to applicable federal and state laws, rules, and regulations as well as company policies and training requirements.
Highmark Health and its affiliates prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities and prohibit discrimination against all individuals based on any category protected by applicable federal, state, or local law.
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For accommodation requests, please contact HR Services Online at HRServices@highmarkhealth.org
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• Work directly with the business to understand their business processes and aims, then identify how analytical solutions could help deliver value for them. This would include being accountable for:
• Outlining complex new use cases + creating high level impact estimates
• Identifying data elements needed and where to get them (including proxies)
• Assembling data sets independently using knowledge of Highmark operational and analytic data structures
• Deliver the analytical solution to a complex business problem
• Documenting objectives, assumptions and processes in line with our standards
• Select and apply the appropriate advanced modeling/machine learning techniques to these data sets to deliver business insight, ensuring that the final analysis is well researched, accurate, and documented. This requires: Experience with a substantial number of advanced analytical techniques and proficiency in a few, evidenced by in-depth knowledge and delivery record (for example regression models, tree-based learning, neural networks, clustering techniques, natural language processing)
• Consult with the business to contextualize and translate the results of our analysis in a form which the business can understand and act upon. This will include: Written reports, presentation and data visualizations, and draws clear lines between the high-level problem specifications for colleagues and stakeholders, the analyses performed, and how the results link directly back to business objectives, and work with colleagues to deliver implementation which drives frontline workflow.
• Plan, prepare and deliver/coordinate all elements of the analysis at the direction of a manager in such a way that it is delivered on time, to a high standard and ready to implement on a production basis (including dissemination through the Organization’s user systems). This includes identifying the best route to implementation (developing the analytical solution accordingly).
• Research self- directed new analytical skills and approaches, building relationships internally and externally to transfer knowledge and maintain their position as subject matter experts, consult with fellow data scientists and analysts to guide analysis and deliver larger projects.
• Other duties as assigned or requested.