Lead the evaluation and continuous improvement of entity resolution and entity linking pipelines.
Debug new builds, identify anomalies, and recommend modeling or system-level improvements.
Define, implement, and maintain scalable performance and quality metrics, leveraging automation and LLM-based approaches where appropriate.
Partner with Engineering to optimize entity linking and ranking systems using Learning-to-Rank and related techniques.
Design methods to assess and classify entity confidence and quality across the graph.
Design and implement a comprehensive data quality framework for graph-based identity data.
Translate abstract quality concepts (e.g., reliability, stability, consistency) into measurable signals.
Identify and operationalize generalized, high-impact predictive signals derived from graph structure, temporal dynamics, and relational patterns.
Collaborate closely with Engineering, Product Management, Compliance, and downstream product teams.
Act as a technical leader within the Identity organization, influencing modeling standards, experimentation rigor, and best practices.

Requirements

Master’s or PhD in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field
5+ years of experience in applied data science, machine learning, or artificial intelligence, with a focus on graph-based modeling and large-scale data systems
Strong proficiency in Python and PySpark
Deep experience with classification models, Learning-to-Rank, Anomaly Detection, Statistical Modeling
Experience building and maintaining production-grade ML systems at scale
Hands-on experience with Databricks
Familiarity with graph databases and query languages such as NeptuneDB and OpenCypher
Experience with graph processing frameworks (e.g., GraphFrames)
Experience applying LLMs for evaluation, automation, or signal discovery (preferred)
Familiarity with Knowledge Graphs and Graph Neural Networks (GNNs) (preferred)

Benefits

Offers Equity
Offers Bonus

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonPySparkclassification modelsLearning-to-RankAnomaly DetectionStatistical Modelinggraph-based modelinglarge-scale data systemsgraph processing frameworksLLMs

Soft Skills

technical leadershipcollaborationinfluencecommunication

Certifications

Master’s in Computer SciencePhD in Computer ScienceMaster’s in Data SciencePhD in Data ScienceMaster’s in Machine LearningPhD in Machine LearningMaster’s in StatisticsPhD in StatisticsMaster’s in MathematicsPhD in Mathematics