Job Overview
Location
Remote - US
Job Type
Full-time
Category
Data Science
Date Posted
April 24, 2026
Full Job Description
đź“‹ Description
- • Senior Data Scientist leading international eKYC and identity graph initiatives to build global identity verification solutions for Socure’s Verify and KYC products.
- • Designing and deploying ML and graph-based algorithms for entity resolution, identity trust scoring, and anomaly detection across heterogeneous, country-specific datasets.
- • Defining and evolving Socure’s international identity graph, including schema design, linkage strategies, quality tiers, and confidence scoring for use across multiple products.
- • Owning experimentation strategy, evaluation frameworks, and model governance for international markets, including offline/online testing, fairness analysis, and regulatory compliance.
- • Leading vendor evaluation and integration of international data sources, ensuring compliance with regional regulations like GDPR and local AML/KYC rules.
- • Collaborating with engineering, product, compliance, and GTM teams to scale eKYC solutions globally using Spark/PySpark, AWS, and MLOps workflows.
- • Mentoring data scientists on international modeling best practices, including handling low-label regimes, domain adaptation, and building reusable abstractions.
- • Communicating technical strategy and results to senior leadership with focus on business impact, regional risk, and regulatory trade-offs.
- • Part of Socure’s mission to build identity trust infrastructure for the digital economy, verifying 100% of good identities in real time and stopping fraud before it starts.
🎯 Requirements
- • Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field, or equivalent practical experience.
- • 6+ years of hands-on applied ML/data science experience (4+ with Ph.D.), including owning production models and pipelines in high-stakes domains such as fraud, risk, identity, payments, or credit.
- • Expert-level proficiency in Python and SQL, with extensive experience in distributed data processing (Spark/PySpark, Databricks) on very large datasets.
- • Deep experience designing, training, and deploying models for classification, ranking, anomaly detection, and/or graph learning, including feature engineering for noisy/heterogeneous identity data and robust evaluation under label sparsity.
- • Proven expertise with graph technologies (e.g., Neo4j, AWS Neptune, GraphFrames, DGL, PyTorch Geometric) and graph algorithms (entity resolution, link prediction, community detection, label propagation) at scale.
- • Significant prior work on international or multi-region products (e.g., cross-country KYC, credit risk, payments, or compliance systems) strongly preferred.
🏖️ Benefits
- • Opportunity to work on high-impact, complex problems in identity trust and fraud prevention with real-world societal impact.
- • Remote work flexibility within the United States (must be within 45 miles of a talent hub).
- • Collaborative, owner-minded culture that values critical thinking, precision, and solving customer problems.
- • Access to cutting-edge tools and infrastructure including AWS, Spark, SageMaker, Neptune, and modern MLOps workflows.
- • Sponsorship not available at this time.
- • Socure is an equal opportunity employer committed to diversity and inclusion, providing accommodations during the application and hiring process upon request.
Skills & Technologies
Python
Go
Neo4j
AWS
PyTorch
Data Science
Senior
Remote
Degree Required
About Socure Inc.
Socure Inc. provides digital identity verification and fraud prevention software for financial services, fintech, e-commerce and government clients. The platform applies machine learning and graph-based analytics to link and validate identity elements in real time, detecting synthetic identities, account takeover and document fraud. It integrates via APIs and SDKs for onboarding, KYC/AML compliance and transaction monitoring, aiming to reduce false positives and manual reviews while improving approval rates for legitimate users worldwide.
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