S

Socure

Digital identity verification and fraud prevention

Data Scientist 2 - Big Data R&D, Identity Graph & Deceased Monitoring

Applied Machine LearningConfirmed live in the last 24 hours
Full-time$140k - $170k /yr

About the Job

Requirements

  • A master's degree with 2+ years of experience, or a 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, such as Python or Scala.
  • Experience writing and optimizing SQL for large datasets and comfort working in data lake or warehouse environments.
  • Hands-on experience with Spark or PySpark and common machine learning libraries.
  • Familiarity with UNIX environments and the AWS ecosystem, including EMR and S3.
  • Working knowledge of supervised and unsupervised machine learning and basic statistics, including similarity measures, clustering, and evaluation metrics.
  • Ability to break down loosely defined problems, ask clarifying questions, and iterate quickly with feedback.
  • Must be located within 45 miles of a talent hub.

Responsibilities

  • Contribute to designing and implementing 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 for deceased monitoring and compliance solutions.
  • Build and maintain data-processing pipeline components, including ETL, feature generation, and normalization, using Spark/PySpark and AWS services such as EMR and S3.
  • Support senior data scientists with feature engineering, data exploration, error analysis, and A/B test setup for new models and signals.
  • Evaluate new third-party and internal data sources by profiling data quality, designing offline experiments, and summarizing effects on coverage and model performance.
  • Implement and maintain SQL and Python or R code for data extraction, transformation, and validation; contribute to code reviews and basic testing.
  • Provide analytical support to compliance and regulatory product teams through ad hoc investigations, simple dashboards, and data deep dives.
  • Communicate findings clearly and in a structured way to peers and cross-functional partners in Product, Engineering, and Client Analysis, focusing on key insights and trade-offs.
  • Own well-scoped tasks and follow them through to completion in a fast-paced, cross-functional environment.

Desired Qualifications

  • Databricks experience.
  • Exposure to graph techniques or graph databases such as Neo4j, AWS Neptune, or GraphFrames.
  • Experience with Elasticsearch or DynamoDB.
  • Experience with workflow tools such as Airflow for automating data pipelines.

About the Company

Socure

Digital identity verification and fraud prevention

Socure provides digital identity verification and fraud prevention services for financial institutions through a subscription-based platform. It uses machine learning and advanced algorithms to analyze small amounts of customer data to predict fraud risk. A flagship feature, the Sigma Fraud Score, compares transactions against a proprietary database of known fraudulent users and traits to detect suspicious activity. Additional tools like Device Risk verify session authenticity by gathering device and browser signals, supporting seamless and secure customer experiences. Socure differentiates itself with a robust, data-driven fraud scoring system, a suite of identity verification and compliance tools, and continuous platform updates delivered as a service. Its goal is to help banks and other lenders verify customers quickly and accurately while reducing fraud and ensuring regulatory compliance (e.g., Customer Identification Programs under the Patriot Act).

Company size
501-1,000
Company stage
Series F
Total funding
$900.1M
Headquarters
Incline Village-Crystal Bay, Nevada
Founded
2012

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