Senior Data Scientist – Big Data R&D, Identity Graph, KYC

🕒 Abril 24

🏄 California – Remoto

🏄 California – Remote

💵 $140.000 - $170.000 / ano

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

🦅 Patrocina Visto H1B

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Socure

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 2012

🤖 Inteligência Artificial

🔐 Segurança

💸 Finanças

💰 $450.000.000 Series E em 2021-11

Artificial Intelligence • Security • Finance

Socure é um fornecedor líder de soluções de verificação de identidade e prevenção de fraude baseadas em IA. Sua plataforma, conhecida como RiskOS™, permite que organizações tomem decisões confiáveis em relação à identidade e risco, permitindo a integração e gestão contínua de clientes em vários pontos de contato. Com verificações de identidade precisas e em tempo real realizadas em mais de 190 países, a Socure ajuda a combater fraudes de identidade, garantindo conformidade e melhorando a experiência do cliente.

Descrição

• Own the design, development, and evaluation of machine learning, statistical, and graph-based algorithms for entity-resolution, identity trust scoring, and anomaly detection on massive datasets. • Architect and optimize graph-based identity representations (identity graph structure, linkage rules, clustering) to improve match rates, reduce false positives/negatives, and support downstream fraud and KYC models. • Build and maintain scalable data pipelines and feature stores in Spark/PySpark (or Scala), including data normalization, deduplication, and feature computation across large PII datasets in AWS/Databricks environments. • Lead A/B tests and offline/online experimentation for new models, features, and data sources; define success metrics, design experiments, and ensure rigorous validation before rollout. • Evaluate new internal and external data sources: explore signal quality, design backtests, quantify incremental value, and provide clear recommendations on vendor selection and integration. • Partner closely with product managers and engineers to translate ambiguous business and regulatory requirements (e.g., KYC coverage, watchlist matching) into concrete modeling and data roadmaps. • Provide deep analytical support to Socure’s compliance and regulatory product suite, including investigative analyses, root‑cause analysis for anomalies, and clear narratives for internal and external stakeholders. • Contribute to model governance and documentation: clearly explain model logic, data dependencies, limitations, and monitoring plans to internal risk/compliance stakeholders. • Mentor junior data scientists and engineers on best practices in data exploration, feature engineering, experimentation, and code quality. • Communicate complex technical concepts and trade‑offs in a concise, structured way to both technical and non‑technical audiences (e.g., product reviews, customer meetings, internal briefings).

🎯 Requisitos

• Master’s degree with 3+ years of relevant industry experience, or Ph.D. with 1+ years of experience in applied ML / data science roles; background in Computer Science, Statistics, Mathematics, or related quantitative fields preferred. • Strong proficiency in Python (preferred) or Scala, including experience with ML libraries such as scikit‑learn, XGBoost, TensorFlow or PyTorch. • Extensive experience with Spark or PySpark and distributed data systems (e.g., AWS EMR, Databricks) working on very large, messy datasets. • Deep understanding of supervised and unsupervised learning, feature engineering, model evaluation, and experiment design (A/B testing, holdout strategies, stratification). • Experience developing production-quality data pipelines and automated workflows using Airflow or similar orchestration tools. • Practical familiarity with graph databases and/or graph frameworks (Neo4j, AWS Neptune, GraphFrames, DGL, PyTorch Geometric) and graph algorithms for clustering, link prediction, and community detection is strongly preferred. • Solid SQL skills and experience working with large-scale analytical data stores. • Experience in at least one of: identity verification, fraud detection, credit risk, or adjacent high‑stakes domains is a plus. • Demonstrated ability to lead medium‑to‑large projects end‑to‑end, make sound trade‑off decisions under ambiguity, and influence cross‑functional stakeholders with data and clear reasoning.

🏖️ Benefícios

• Offers Equity • Offers Bonus