Socure
Staff Data Scientist - Digital Intelligence
Hybrid - US · Staff+
Sponsorship not specifiedDetected 6 days ago
PythonSQLMachine LearningTensorFlowPyTorchscikit-learnSparkData ScienceMLOpsStatisticsVPNLeadershipCommunicationMentoringRisk Modeling
About the role
- Socure is the leading provider of digital identity verification and fraud prevention solutions, using AI and machine learning to power accurate identity trust decisions.
- Our mission is to eliminate identity fraud and ensure online trust across industries.
- We are seeking a Staff Data Scientist to join our Digital Intelligence team.
Responsibilities
- Build and guide scalable feature-engineering approaches for high-cardinality, sparse, noisy, and platform-dependent telemetry.
- Define evaluation methods for Digital Intelligence signals, including holdout design, leakage checks, drift monitoring, adversarial robustness, customer impact analysis, and long-term signal stability.
- Communicate technical recommendations, tradeoffs, limitations, and results clearly to data science peers, engineering partners, product stakeholders, risk teams, and senior leadership.
- Socure is building the identity trust infrastructure for the digital economy - verifying 100% of good identities in real time and stopping fraud before it starts.
Requirements
- Strong proficiency in Python and distributed data processing frameworks such as Spark, PySpark, or equivalent tools.
- Demonstrated ability to work with imperfect labels, delayed outcomes, telemetry artifacts, instrumentation gaps, and changing fraud patterns.
- Experience influencing data architecture, instrumentation, feature logging, and product direction through technical credibility rather than direct authority.
- Excellent communication skills, including the ability to explain complex data science decisions and risk tradeoffs to technical and non-technical audiences.
- Strong mentorship skills and a track record of improving the technical quality and judgment of other data scientists.
- Own ambiguous fraud and identity risk problems where data quality, label reliability, adversarial behavior, customer impact, and product tradeoffs must be evaluated together.
- Mentor data scientists by improving problem framing, modeling judgment, validation rigor, code quality, and ability to operate independently in ambiguous domains.
Nice to have
- Experience with device intelligence, browser/mobile fingerprinting, behavioral biometrics, network intelligence, VPN/proxy detection, entity resolution, or graph-based risk signals.
- Experience with streaming, near-real-time, or low-latency decisioning systems.
- Familiarity with adversarial modeling, robust ML, privacy-preserving ML, interpretable ML, or responsible AI practices.
- Hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar.
- Experience setting standards for model explainability, feature governance, validation methodology, or production ML observability.
- Socure is an equal opportunity employer that values diversity in all its forms within our company.
- YouTube https://www.youtube.com/c/Socure | LinkedIn https://www.linkedin.com/company/socure/ | X (Twitter) https://x.com/socureme | Facebook https://www.facebook.com/socure/
Skills
- Expert-level SQL skills and extensive experience working with large-scale, complex, noisy datasets.
Benefits
- Lead high-impact machine learning and feature-development initiatives across device, network, browser, mobile, session, and behavioral intelligence.
- Develop production risk signals and models that balance fraud detection, false-positive risk, coverage, latency, explainability, robustness, and operational maintainability.
Company info
- The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
This listing is sourced directly from Socure's careers page and normalized into a canonical job model.