Lead Data Scientist - Research and Development - Graph Intelligence

Highmark Health; United States; Remote; USD 108,000 - 202,000; Full time

Job summary

A leading healthcare organization is seeking a Lead Data Scientist specializing in Graph Intelligence. You will drive innovative analytical solutions utilizing network science and Graph Machine Learning, with responsibilities including outlining use cases, applying advanced modeling techniques, and mentoring others. The role requires a Master's degree or higher in a related field and significant experience in Data Science. This position offers competitive compensation ranging from $108,000 to $201,800.

Qualifications

• Master's degree in a related field or Bachelor's with 3 years of relevant experience.
• 5 years of experience in Data Science.
• Deep expertise in Graph Theory & Network Science.

Responsibilities

• Outline complex new use cases and create high-level impact estimates.
• Apply advanced modeling/machine learning techniques to deliver business insight.
• Consult with the business to translate results into actionable insights.

Skills

Analysis of business problems/needs

Analytical and logical reasoning

Collaborative problem solving

Data analysis with SQL

Statistical analysis with Python

Written and oral presentation skills

Education

Master's degree in Analytics or related field

PhD in Analytics or related field

Tools

Neo4j

Apache Spark GraphX

DGL

BigQuery

Job description

Overview

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 Lead Data Scientist, Research & Development, specializing in Graph Intelligence, who will define the future of harnessing relational insights in healthcare. This is a premier R&D position leading the charge in inventing transformative graph-native analytical solutions and pioneering novel methodologies that leverage network science, knowledge graphs, and Graph Machine Learning (GML) to solve problems across the healthcare continuum.

You will work on graph theory, knowledge graphs, Graph Neural Networks (GNNs), graph convolutional networks (GCNs), and graph attention networks (GATs). You will architect graph embeddings, perform link prediction, community detection, and anomaly detection on complex healthcare data, design rigorous experiments, and evaluate performance and interpretability for real-world applicability.

As a relational data innovator with a strategic mindset, you will construct and leverage comprehensive healthcare knowledge graphs that integrate diverse patient, provider, claims, and clinical data to uncover hidden patterns and insights that inform analytic solutions in healthcare.

You will leverage expertise in graph databases (e.g., Neo4j, ArangoDB, Amazon Neptune, Ontotext GraphDB), distributed graph processing (e.g., Apache Spark GraphX, Dask-Graph), and GML libraries (e.g., PyTorch Geometric, DGL, Spektral) to conduct research, build predictive, prescriptive, and diagnostic models on graph structures, and drive initiatives from concept to scalable prototypes. You will stay current with the graph AI landscape, evaluate emerging platforms and tools, and collaborate with academic and healthcare researchers, contributing to publications and leading discussions on graph intelligence in healthcare.

Essential Responsibilities

• Work with the business to understand processes and aims, identify how analytical solutions can deliver value, and be accountable for:
  • Outlining complex new use cases and creating high-level impact estimates
  • Identifying needed data elements and sources (including proxies)
  • Assembling datasets using knowledge of Highmark operational and analytic data structures
  • Delivering analytical solutions to multiple complex business problems
  • Documenting objectives, assumptions, and processes; expanding standards as needed

• Select and apply advanced modeling/machine learning techniques to these data sets to deliver business insight; demonstrate proficiency across techniques with depth in several areas (e.g., regression, tree-based methods, neural networks, clustering, NLP)

• Consult with the business to contextualize and translate results into actionable insights, including written reports, presentations, data visualizations, and linking analyses to business objectives to drive frontline workflow

• Plan, prepare, and deliver analyses largely independently, on time and to production-ready standards; identify the best route to implementation

• Be the face of major projects within ED&A, contribute to external presence (conferences, white papers, associations), mentor others

• Other duties as assigned or requested

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)

Preferred

• Deep Expertise in Graph Theory & Network Science: Centrality, community detection, pathfinding, clustering; knowledge graph principles and network analysis for complex systems
• Advanced Graph ML (GML): Designing and optimizing GNN architectures for tasks like node classification, link prediction, anomaly detection
• Knowledge Graph Engineering: Ontologies, RDF/OWL, data ingestion, entity resolution, graph querying (Cypher, SPARQL)
• Graph Database & Platform Experience: Neo4j, Google Spanner Graph, and distributed graph processing
• GML Libraries & Frameworks: PyG, DGL, Spektral, StellarGraph
• Cloud & MLOps: Deploying and managing GML pipelines in cloud environments with MLOps practices
• Research & Publication: Track record of publications or driving novel solutions to prototype
• Healthcare Data Familiarity: Claims, clinical, EMR; familiarity with SNOMED CT, ICD
• Experimental Design & Rigor: Robust experiments, rigorous evaluation, interpretable results

Licenses or Certifications

Required

• None

Preferred

• None

Skills

• Analysis of business problems/needs
• Analytical and logical reasoning
• Collaborative problem solving
• Data analysis with SQL, BigQuery
• Statistical analysis with Python, R
• Written and oral presentation skills
• Basic prototyping/front-end skills

Travel

0% – 25%

Working Conditions

Office-based; occasional teaching/mentoring; travel between sites as needed; physical demands listed below

Physical: lifting up to 10 pounds frequently; lifting 10–25 pounds occasionally; lifting 25–50 pounds rarely

Position constraints and compliance: this role adheres to HIPAA, privacy policies, and the company code of conduct; accessibility and accommodation information provided below

Disclaimer: The job description reflects the general nature and essential duties; not an exhaustive list

Compliance: Adherence to ethical and legal standards as per the code of business conduct and policies

Pay Range Minimum: $108,000.00

Pay Range Maximum: $201,800.00

Base pay is determined by qualifications, experience, and internal/external market considerations. Salary ranges may vary by location.

Highmark Health and affiliates prohibit discrimination based on protected status and commit to accessibility for applicants; for accommodations or accessibility contact HR Services.
HR Services email: [e-mail]