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Staff Data Scientist - Digital Intelligence

SocureHybrid - San Francisco, CAAI and Data
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Salary
$191K - $230K USD
Job type
Full-time
Posted
27 Jul 2026
Status
Open · checked 9d ago

About this role

The Staff Data Scientist - Digital Intelligence position at Socure is a hands-on technical leadership role based out of San Francisco, California, on a hybrid schedule. This opportunity is well-suited for an experienced data science expert who wants to shape the future of digital identity verification and fraud prevention.

Role Overview

In this hybrid position, the professional provides technical leadership by transforming high-scale device, network, browser, mobile, API, and behavioral telemetry into production-grade fraud and identity risk signals. The candidate owns ambiguous identity risk challenges where data quality, label reliability, adversarial behavior, and product tradeoffs intersect. Responsibilities include defining rigorous evaluation methods, influencing telemetry collection, and setting technical directions to detect risky behavior and recognize trustworthy sessions.

Key Responsibilities

Lead high-impact machine learning and feature-development initiatives covering device, network, browser, mobile, session, and behavioral intelligence.
Build production risk signals and models balancing fraud detection, false-positive risk, coverage, latency, explainability, robustness, and maintainability.
Guide scalable feature-engineering approaches for high-cardinality, sparse, noisy, and platform-dependent telemetry.
Investigate complex signal patterns including spoofing, emulator behavior, automation, proxy or VPN usage, and low-entropy fingerprints.
Define evaluation methods such as holdout design, leakage checks, drift monitoring, adversarial robustness, and long-term signal stability.
Partner with engineering, product, and risk teams to influence telemetry collection, data contracts, and production readiness.
Translate open-ended business questions into clear data science approaches and production-ready signal roadmaps.
Communicate technical recommendations and tradeoffs clearly to peers, stakeholders, and senior leadership.
Mentor fellow data scientists by improving problem framing, modeling judgment, and validation rigor.

Requirements

Hold a Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or a related quantitative field.
Bring 12 or more years of professional experience in data science, applied machine learning, statistical modeling, or related technical roles.
Significant hands-on experience building, deploying, validating, and improving production machine learning models and risk signals.
Strong background in fraud detection, identity verification, trust and safety, anomaly detection, cybersecurity, or risk modeling.
Expert-level SQL skills combined with extensive experience managing large-scale, complex, and noisy datasets.
Strong proficiency in Python alongside distributed data processing frameworks such as Spark or PySpark.
Deep understanding of supervised and unsupervised learning, anomaly detection, feature engineering, and statistical validation.
Demonstrated capability to handle imperfect labels, delayed outcomes, and shifting fraud patterns.
Proven ability to influence data architecture and product direction through technical credibility.
Excellent communication and mentorship skills.

Nice to Have

Experience working with device intelligence, mobile fingerprinting, behavioral biometrics, network intelligence, or graph-based risk signals.
Background in designing features from high-cardinality categorical data using embeddings, target encoding, or representation learning.
Exposure to streaming or near-real-time low-latency decisioning systems.
Familiarity with adversarial modeling, robust machine learning, privacy-preserving techniques, or interpretable artificial intelligence.
Hands-on usage of frameworks like scikit-learn, XGBoost, TensorFlow, or PyTorch.
Experience setting standards for model explainability and feature governance.

Skills and Tools

Python
PyTorch
TensorFlow
SQL
Spark
PySpark
Scikit-learn
XGBoost

Salary and Benefits

Annual Salary: $191,000 to $230,000 in USD per year.

About the Company

Socure builds the identity trust infrastructure for the digital economy, aiming to verify 100 percent of good identities in real time while stopping fraud before it begins. The company values individuals who act like owners, move fast, think critically, and care deeply about solving complex customer problems with precision.

How to Apply

Interested candidates should visit the official Socure careers page to submit an application for this position.

Skills and tech stack

PythonPyTorchTensorFlowSQLSpark

Questions candidates ask

What is the salary range for the Staff Data Scientist position?

The annual salary for this role ranges from $191,000 to $230,000 USD.

Where is this job located?

This role is offered on a hybrid basis located in San Francisco, California.

What level of experience is required?

Candidates must have 12+ years of experience in data science, applied machine learning, statistical modeling, or related technical roles, along with a Master's or Ph.D. in a quantitative field.

What technical skills are necessary for this role?

Required technical skills include expert-level SQL, strong proficiency in Python, experience with distributed data processing frameworks like Spark or PySpark, and deep understanding of machine learning models and risk signals.

How do I apply for the role?

Applicants should apply directly on the official Socure careers page.

Ready to apply?

The application is on the official Socure careers page.

Apply on company site