Highmark Health
Lead Data Scientist - Research and Development - Graph Intelligence
Highmark Health, Boston, Massachusetts, us, 02298
Overview
Company :
Highmark Health Job Description : JOB SUMMARY Are you an architect of interconnected data, driven by the belief that relationships hold the key to uncovering society's most complex challenges? Highmark Health is seeking a groundbreaking Lead Data Scientist, Research & Development, specializing in Graph Intelligence, who will not just work with graph data, but will define the future of how we harness relational insights in healthcare. This is a premier R&D position where you will lead the charge in inventing and proving out transformative graph-native analytical solutions. Your core mission is to push the boundaries of what's possible in advanced analytics by pioneering novel methodologies that leverage network science, knowledge graphs, and Graph Machine Learning (GML) to solve critical problems across the healthcare continuum. From personalizing patient care pathways to detecting complex fraud rings and understanding population health dynamics, your work will directly impact millions of lives. As our Lead Graph Intelligence specialist, you will be the spearhead of cutting-edge research projects. This means deeply engaging with graph theory, building and enriching large-scale knowledge graphs, and developing next-generation Graph Neural Networks (GNNs), graph convolutional networks (GCNs), graph attention networks (GATs), and other advanced network algorithms. You'll architect unique graph embeddings, perform sophisticated link prediction, community detection, and anomaly detection on complex healthcare data. Your responsibilities will include designing rigorous experiments, building robust proof-of-concept models, and evaluating the performance and interpretability of these novel graph algorithms to ensure real-world applicability. You are not merely a data scientist; you are a relational data innovator with a strategic mindset. You inherently understand that the explicit modeling of entities and their relationships unlocks a deeper layer of intelligence that traditional tabular or sequential data models cannot. You will proactively identify opportunities to construct and leverage comprehensive healthcare knowledge graphs, integrating diverse patient, provider, claims, and clinical data to uncover hidden patterns, propagate insights through networks, and develop analytical solutions that exploit the rich, multi-modal structures within healthcare. Leveraging your profound expertise in graph databases (e.g., Neo4j, ArangoDB, Amazon Neptune, Ontotext GraphDB), distributed graph processing frameworks (e.g., Apache Spark GraphX, Dask-Graph), and leading GML libraries (e.g., PyTorch Geometric, DGL, Spektral), you will conduct in-depth research, construct predictive, prescriptive, and diagnostic models directly on graph structures. You will drive initiatives from theoretical concept to validated, scalable prototypes. You are a vigilant scout of the graph AI landscape, continuously evaluating and championing the adoption of emerging graph platforms, algorithms, and tools. You will foster collaborations with leading academic institutions, healthcare research experts, and the broader graph community. Your contributions may include publishing seminal research findings in top-tier conferences and leading the dialogue on the transformative power of graph intelligence in healthcare.
Essential Responsibilities
Work directly with the business to understand processes and aims, then identify how analytical solutions could deliver value. This includes being accountable for: Outlining complex new use cases and creating high-level impact estimates. Identifying data elements needed and where to obtain them (including proxies). Assembling data sets independently using knowledge of Highmark operational and analytic data structures. Delivering analytical solutions to several complex business problems simultaneously. Documenting objectives, assumptions and processes and enriching/expanding standards as needed. Selecting and applying appropriate advanced modeling/machine learning techniques to these data sets to deliver business insight, with proficiency in a substantial number of techniques (e.g., regression, tree-based methods, neural networks, clustering, natural language processing). Consulting with the business to contextualize and translate results into actionable insights via written reports, presentations, and data visualizations; linking analyses to business objectives and leading implementation decisions that drive frontline workflow. Planning and delivering elements of several analyses largely independently, on time and to a production-ready standard, including identifying the best route to implementation. Being a subject-matter expert and a face of major projects within ED&A; mentoring and teaching others; engaging in external presence (conferences, publications). Other duties as assigned.
Education
Required Master's degree in Analytics, Mathematics, Physics, Computer and Information Science, Engineering Technology or related field OR Bachelor's Degree + 3 years of relevant work experience in lieu of a Master's Degree Preferred Doctoral degree (Ph.D.) in Analytics, Mathematics, Physics, Computer and Information Science, Engineering Technology, or a related field.
Experience
Required 5 years of Data Science 3 years Data Science (if PhD Educational) Preferred Deep Expertise in Graph Theory & Network Science: Understanding of graph algorithms, knowledge graph principles, and network analysis for complex systems. Advanced Graph Machine Learning (GML): Experience designing and optimizing Graph Neural Networks and related models for tasks like node classification, link prediction, and anomaly detection. Knowledge Graph Engineering: Lifecycle of knowledge graphs including schema design, ingestion, construction, cleaning, entity resolution, and graph querying. Graph Database & Platform Experience: Experience with leading graph databases (e.g., Neo4j, Google Spanner Graph) and distributed graph processing. GML Libraries & Frameworks: Proficiency with PyTorch Geometric, DGL, Spektral, or StellarGraph. Cloud Platform & MLOps: Experience deploying ML models in cloud environments and familiarity with MLOps principles. Research & Publication Acumen: Track record of contributing to research or driving novel solution development from concept to prototype. Healthcare Data Familiarity: Understanding of healthcare data domains (claims, clinical, EMR) and related standards (e.g., SNOMED CT, ICD) is a plus. Experimental Design & Rigor: Ability to design robust experiments and interpret results.
Licenses or Certifications
Required None Preferred None
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 prototyping/front-end skills
Language
Other than English: None
Travel
0% - 25%
Physical, Mental Demands and Working Conditions
Position Type: Office-Based Teaches / trains others regularly: Occasionally Travel regularly from the office to various work sites: Never Sales roles and related physical requirements: Never Physical work site required: No Lifting: up to 10 pounds — Frequently; 10 to 25 pounds — Occasionally; 25 to 50 pounds — Rarely
Disclaimer: The job description indicates the general nature and essential duties and responsibilities of work performed by employees in this title. It may not contain a comprehensive inventory of all duties, responsibilities, and qualifications required. Compliance Requirement: This position adheres to ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies. HIPAA and Privacy: As a component of job responsibilities, employees may have access to sensitive information and must comply with HIPAA and the company’s privacy and security policies. Code of Conduct: Employees must comply with the company’s Code of Business Conduct and applicable laws and policies.
Pay
Pay Range Minimum: $108,000.00 Pay Range Maximum: $201,800.00 Note: Base pay is determined by qualifications, experience, and other factors; the salary range may vary by location. Discrimination Notice: Highmark Health and its affiliates prohibit discrimination based on protected status and other local laws. Accessibility and accommodation information available via HR contact. Req ID: J267786
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Company :
Highmark Health Job Description : JOB SUMMARY Are you an architect of interconnected data, driven by the belief that relationships hold the key to uncovering society's most complex challenges? Highmark Health is seeking a groundbreaking Lead Data Scientist, Research & Development, specializing in Graph Intelligence, who will not just work with graph data, but will define the future of how we harness relational insights in healthcare. This is a premier R&D position where you will lead the charge in inventing and proving out transformative graph-native analytical solutions. Your core mission is to push the boundaries of what's possible in advanced analytics by pioneering novel methodologies that leverage network science, knowledge graphs, and Graph Machine Learning (GML) to solve critical problems across the healthcare continuum. From personalizing patient care pathways to detecting complex fraud rings and understanding population health dynamics, your work will directly impact millions of lives. As our Lead Graph Intelligence specialist, you will be the spearhead of cutting-edge research projects. This means deeply engaging with graph theory, building and enriching large-scale knowledge graphs, and developing next-generation Graph Neural Networks (GNNs), graph convolutional networks (GCNs), graph attention networks (GATs), and other advanced network algorithms. You'll architect unique graph embeddings, perform sophisticated link prediction, community detection, and anomaly detection on complex healthcare data. Your responsibilities will include designing rigorous experiments, building robust proof-of-concept models, and evaluating the performance and interpretability of these novel graph algorithms to ensure real-world applicability. You are not merely a data scientist; you are a relational data innovator with a strategic mindset. You inherently understand that the explicit modeling of entities and their relationships unlocks a deeper layer of intelligence that traditional tabular or sequential data models cannot. You will proactively identify opportunities to construct and leverage comprehensive healthcare knowledge graphs, integrating diverse patient, provider, claims, and clinical data to uncover hidden patterns, propagate insights through networks, and develop analytical solutions that exploit the rich, multi-modal structures within healthcare. Leveraging your profound expertise in graph databases (e.g., Neo4j, ArangoDB, Amazon Neptune, Ontotext GraphDB), distributed graph processing frameworks (e.g., Apache Spark GraphX, Dask-Graph), and leading GML libraries (e.g., PyTorch Geometric, DGL, Spektral), you will conduct in-depth research, construct predictive, prescriptive, and diagnostic models directly on graph structures. You will drive initiatives from theoretical concept to validated, scalable prototypes. You are a vigilant scout of the graph AI landscape, continuously evaluating and championing the adoption of emerging graph platforms, algorithms, and tools. You will foster collaborations with leading academic institutions, healthcare research experts, and the broader graph community. Your contributions may include publishing seminal research findings in top-tier conferences and leading the dialogue on the transformative power of graph intelligence in healthcare.
Essential Responsibilities
Work directly with the business to understand processes and aims, then identify how analytical solutions could deliver value. This includes being accountable for: Outlining complex new use cases and creating high-level impact estimates. Identifying data elements needed and where to obtain them (including proxies). Assembling data sets independently using knowledge of Highmark operational and analytic data structures. Delivering analytical solutions to several complex business problems simultaneously. Documenting objectives, assumptions and processes and enriching/expanding standards as needed. Selecting and applying appropriate advanced modeling/machine learning techniques to these data sets to deliver business insight, with proficiency in a substantial number of techniques (e.g., regression, tree-based methods, neural networks, clustering, natural language processing). Consulting with the business to contextualize and translate results into actionable insights via written reports, presentations, and data visualizations; linking analyses to business objectives and leading implementation decisions that drive frontline workflow. Planning and delivering elements of several analyses largely independently, on time and to a production-ready standard, including identifying the best route to implementation. Being a subject-matter expert and a face of major projects within ED&A; mentoring and teaching others; engaging in external presence (conferences, publications). Other duties as assigned.
Education
Required Master's degree in Analytics, Mathematics, Physics, Computer and Information Science, Engineering Technology or related field OR Bachelor's Degree + 3 years of relevant work experience in lieu of a Master's Degree Preferred Doctoral degree (Ph.D.) in Analytics, Mathematics, Physics, Computer and Information Science, Engineering Technology, or a related field.
Experience
Required 5 years of Data Science 3 years Data Science (if PhD Educational) Preferred Deep Expertise in Graph Theory & Network Science: Understanding of graph algorithms, knowledge graph principles, and network analysis for complex systems. Advanced Graph Machine Learning (GML): Experience designing and optimizing Graph Neural Networks and related models for tasks like node classification, link prediction, and anomaly detection. Knowledge Graph Engineering: Lifecycle of knowledge graphs including schema design, ingestion, construction, cleaning, entity resolution, and graph querying. Graph Database & Platform Experience: Experience with leading graph databases (e.g., Neo4j, Google Spanner Graph) and distributed graph processing. GML Libraries & Frameworks: Proficiency with PyTorch Geometric, DGL, Spektral, or StellarGraph. Cloud Platform & MLOps: Experience deploying ML models in cloud environments and familiarity with MLOps principles. Research & Publication Acumen: Track record of contributing to research or driving novel solution development from concept to prototype. Healthcare Data Familiarity: Understanding of healthcare data domains (claims, clinical, EMR) and related standards (e.g., SNOMED CT, ICD) is a plus. Experimental Design & Rigor: Ability to design robust experiments and interpret results.
Licenses or Certifications
Required None Preferred None
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 prototyping/front-end skills
Language
Other than English: None
Travel
0% - 25%
Physical, Mental Demands and Working Conditions
Position Type: Office-Based Teaches / trains others regularly: Occasionally Travel regularly from the office to various work sites: Never Sales roles and related physical requirements: Never Physical work site required: No Lifting: up to 10 pounds — Frequently; 10 to 25 pounds — Occasionally; 25 to 50 pounds — Rarely
Disclaimer: The job description indicates the general nature and essential duties and responsibilities of work performed by employees in this title. It may not contain a comprehensive inventory of all duties, responsibilities, and qualifications required. Compliance Requirement: This position adheres to ethical and legal standards and behavioral expectations as set forth in the code of business conduct and company policies. HIPAA and Privacy: As a component of job responsibilities, employees may have access to sensitive information and must comply with HIPAA and the company’s privacy and security policies. Code of Conduct: Employees must comply with the company’s Code of Business Conduct and applicable laws and policies.
Pay
Pay Range Minimum: $108,000.00 Pay Range Maximum: $201,800.00 Note: Base pay is determined by qualifications, experience, and other factors; the salary range may vary by location. Discrimination Notice: Highmark Health and its affiliates prohibit discrimination based on protected status and other local laws. Accessibility and accommodation information available via HR contact. Req ID: J267786
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