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Data Analyst, Graph Analytics & Machine Learning
Keeper Security
- United States
- United States
Über
Keeper Security is seeking a Data Analyst to join the AI & Threat Analytics team and support the development of KeeperAI Guardian, our AWS Neptunebased knowledge graph for behavioral threat detection and analysis. This is a 100% remote position, with an opportunity to work a hybrid schedule for candidates based in the El Dorado Hills, CA or Chicago, IL metro areas. Keeper's cybersecurity software is trusted by millions of people and thousands of organizations globally. Join one of the fastest-growing cybersecurity companies and play a key role in preparing and analyzing graph-based security data that directly supports machine learning models and threat research. As a Data Analyst on the KeeperAI Guardian team, you will act as the bridge between raw graph data and actionable threat intelligence. You will work hands-on with AWS Neptune, writing complex Gremlin queries to extract insights, validate entity relationships, and uncover behavioral patterns in security telemetry data. Your analysis will directly support ML engineers and security researchers building models for anomaly detection, threat classification, and behavioral risk scoring. Responsibilities Query and analyze complex graph data in AWS Neptune using Gremlin Develop and maintain Python-based scripts for data extraction, cleaning, transformation, and exploratory analysis Perform data validation, profiling, and consistency checks across multiple data sources and entity types Define and document entity relationships, schema mappings, and graph traversal patterns Produce curated datasets for machine learning model training, evaluation, and threat research Identify data quality issues, missing relationships, anomalous patterns, and signal gaps through exploratory analysis Create and maintain query templates, analysis notebooks, and data lineage documentation Collaborate with data engineers and ML engineers to refine data models and improve graph structure Requirements 24+ years of experience in data analysis, data operations, or graph data management in a technical environment Strong proficiency in Python for data manipulation and analysis (Pandas, NumPy) Hands-on experience writing and optimizing Gremlin queries for graph traversal Experience working with graph databases such as AWS Neptune, Neo4j, TigerGraph, or similar Solid understanding of data modeling, entity-relationship design, and graph traversal logic Experience working with complex data pipelines in Python-based environments Working knowledge of SQL as a supporting data analysis tool Strong analytical reasoning and ability to communicate technical findings to diverse audiences Familiarity with cloud platforms (AWS preferred) Bachelor's degree in Data Science, Computer Science, or a related field, or equivalent experience Due to FedRAMP requirements, candidates must be a U.S. Person Keeper Security, Inc. is an equal opportunity employer and participant in the U.S. Federal E-Verify program. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Sprachkenntnisse
- English
Hinweis für Nutzer
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