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

🕒 Abril 24

🏄 California – Remoto

🏄 California – Remote

💵 $140.000 - $170.000 / ano

⏰ Tempo Integral

🟢 Júnior

🟡 Pleno

📊 Cientista de Dados

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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

• Contribute to the design and implementation of machine learning, data mining, statistical, and graph-based algorithms to analyze very large datasets for identity verification and anomaly detection. • Analyze large datasets to help develop and refine entity-resolution and identity-matching algorithms that drive Socure’s KYC and compliance solutions. • Build and maintain components of data-processing pipelines (ETL, feature generation, normalization) using tools such as Spark/PySpark and AWS (e.g., EMR, S3). • Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for new models and signals. • Help evaluate new third‑party and internal data sources: profile data quality, design offline experiments, and summarize impact on coverage and model performance. • Implement and maintain SQL and Python/R code for data extraction, transformation, and validation; contribute to code reviews and basic testing. • Provide analytical support to compliance and regulatory product teams, including ad hoc investigations, simple dashboards, and data deep dives. • Communicate findings in a clear, structured way to peers and cross‑functional partners (Product, Engineering, Client Analysis), focusing on key insights and trade‑offs. • Work effectively in a fast‑paced, cross‑functional environment; demonstrate ownership of well-scoped tasks and follow through to completion.

🎯 Requisitos

• Master’s degree with 2+ years of experience, or Ph.D. with 1+ years of experience in a data science or analytics role, or equivalent practical experience. • Proficiency in at least one general-purpose programming language used in data science (Python, or Scala). • Solid experience writing and optimizing SQL for large datasets; comfort working in data lake / warehouse environments. • Hands‑on experience with Spark or PySpark and common ML libraries (e.g., scikit‑learn, XGBoost, TensorFlow/PyTorch a plus). • Familiarity with UNIX environments and the AWS ecosystem (e.g., EMR, S3); Databricks experience is a plus. • Working knowledge of supervised/unsupervised ML and basic statistics (similarity measures, clustering, evaluation metrics). • Exposure to graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames) is a strong plus. • Bonus: experience with Elasticsearch or DynamoDB; workflow tools such as Airflow for automating data pipelines. • Ability to break down loosely defined problems, ask good clarifying questions, and iterate quickly with feedback.

🏖️ Benefícios

• Offers Equity • Offers Bonus