Socure

1 week ago

Staff Data Scientist - Digital Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Lead technical development of fraud and identity risk signals for the Digital Intelligence team, turning noisy, high-scale device, network, browser, mobile, API, and behavioral telemetry into production-grade models. Own ambiguous, adversarial problems end-to-end—evaluation design, signal strategy, feature engineering, model monitoring, and rollout—while partnering with engineering, product, risk, and platform teams and mentoring other data scientists.

Location: San Francisco, Seattle, New York, Miami, Washington DC

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead high-impact machine learning and feature-development initiatives across device, network, browser, mobile, session, and behavioral intelligence.
•Own ambiguous fraud and identity risk problems, evaluating data quality, label reliability, adversarial behavior, customer impact, and product tradeoffs together.
•Develop production risk signals and models balancing fraud detection, false-positive risk, coverage, latency, explainability, robustness, and operational maintainability.
•Investigate complex signal patterns including spoofing, emulator behavior, automation, proxy/VPN usage, low-entropy fingerprints, telemetry gaps, device fragmentation, and over-linkage risk.
•Define evaluation methods for signals (holdout design, leakage checks, drift monitoring, adversarial robustness, customer impact analysis, long-term stability) and communicate results/tradeoffs while mentoring others.

Pay and Benefits

Salary: USD 191,000 - 230,000 annually

Equity and Bonus:Equity

Perks:EquityAnnual Bonus

Key Requirements

•Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or a related quantitative field.
•12+ years of experience in data science, applied machine learning, statistical modeling, or related technical roles.
•Significant experience building, deploying, validating, and improving production machine learning models, risk signals, or decisioning systems.
•Strong background in fraud detection and identity verification, including trust and safety and adversarial data domains.
•Expert-level SQL and strong proficiency in Python with distributed data processing frameworks such as Spark or PySpark.

Experience:12+ yearsDigital identity verificationFraud detectionMachine learningRisk modelingTrust and safety

Education:Master's

Skills:Critical thinkingCommunicationMentorshipOwnershipTechnical leadership

Tech Stack:PythonSQLSparkPySparkScikit-learnXGBoostTensorFlowPyTorch

Company Brief

Socure

Provides AI-driven digital identity verification and fraud prevention solutions that analyze device, behavioral, and contextual data to detect synthetic identities, stop account takeover, and enable secure onboarding for banks, fintechs, and enterprises.

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: New York, United States

Founded: 2012

Glassdoor: 4.1

Website LinkedIn

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Socure

1 week ago

Staff Data Scientist - Digital Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: San Francisco, Seattle, New York, Miami, Washington DC

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Lead high-impact machine learning and feature-development initiatives across device, network, browser, mobile, session, and behavioral intelligence.
•Own ambiguous fraud and identity risk problems, evaluating data quality, label reliability, adversarial behavior, customer impact, and product tradeoffs together.
•Develop production risk signals and models balancing fraud detection, false-positive risk, coverage, latency, explainability, robustness, and operational maintainability.
•Investigate complex signal patterns including spoofing, emulator behavior, automation, proxy/VPN usage, low-entropy fingerprints, telemetry gaps, device fragmentation, and over-linkage risk.
•Define evaluation methods for signals (holdout design, leakage checks, drift monitoring, adversarial robustness, customer impact analysis, long-term stability) and communicate results/tradeoffs while mentoring others.

Pay and Benefits

Salary: USD 191,000 - 230,000 annually

Equity and Bonus:Equity

Perks:EquityAnnual Bonus

Key Requirements

•Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Data Science, or a related quantitative field.
•12+ years of experience in data science, applied machine learning, statistical modeling, or related technical roles.
•Significant experience building, deploying, validating, and improving production machine learning models, risk signals, or decisioning systems.
•Strong background in fraud detection and identity verification, including trust and safety and adversarial data domains.
•Expert-level SQL and strong proficiency in Python with distributed data processing frameworks such as Spark or PySpark.

Experience:12+ yearsDigital identity verificationFraud detectionMachine learningRisk modelingTrust and safety

Education:Master's

Skills:Critical thinkingCommunicationMentorshipOwnershipTechnical leadership

Tech Stack:PythonSQLSparkPySparkScikit-learnXGBoostTensorFlowPyTorch

Company Brief

Socure

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: New York, United States

Founded: 2012

Glassdoor: 4.1

Website LinkedIn