Lead Fraud Analytics Specialist

2 weeks ago

Mountain View, California, United States ID Inc Full time
Company Overview

ID Inc. is a rapidly expanding enterprise software firm dedicated to streamlining the process of online identity verification and sharing. Our mission is to empower individuals to manage their personal data through a secure and portable login system, eliminating the need for multiple passwords across various platforms. With a digital identity network boasting over 117 million registered users, our services are trusted by numerous federal agencies and over 600 corporations for secure identity verification.

Our technology adheres to federal standards for consumer authentication, receiving recognition as a NIST IAL2 / AAL2 credential service provider. We are committed to inclusivity through our "No Identity Left Behind" initiative, which aims to enhance digital access for underserved communities. Our diverse verification pathways include online self-service, live video support, and in-person assistance, reflecting our dedication to building a comprehensive identity network.

Recently, we have been honored with accolades such as Deloitte's Technology Fast 500 and Entrepreneur Magazine's 100 Brilliant Companies. Our successful Series D funding round has brought our total investment to over $275 million since our inception.

Position Overview

We are on the lookout for a Fraud Analytics Specialist to extract vital insights and identify fraudulent patterns within our network. This role involves close collaboration with the Fraud Analytics Team, Fraud Investigations Team, Engineering, Product, and Customer Success departments to implement our fraud prevention strategy. If you possess a data-driven mindset and a passion for resolving fraud-related challenges, this position is tailored for you.

Key Responsibilities

  • Collaborate with fraud leadership and investigators to refine our fraud prevention strategy.
  • Design and execute experiments, test hypotheses, and analyze fraud patterns to enhance detection methods while minimizing false positives.
  • Utilize data analytics to assess, recommend, and oversee fraud prevention strategies across the network.
  • Quickly respond to fraud incidents by developing monitoring frameworks, dashboards, and solutions in partnership with cross-functional teams.
  • Propose and implement automated rules and models to bolster fraud detection and prevention efforts.
  • Analyze signals and data from member interactions to identify instances of stolen Personal Identifiable Information (PII), social engineering, and account takeovers.
  • Establish robust monitoring systems to ensure optimal performance of both automated and manual fraud detection processes.
  • Foster strong relationships with key stakeholders and leadership.

Qualifications

  • A minimum of 2 years of hands-on experience in fraud analytics or within a high-tech startup environment.
  • Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
  • Master's degree (PhD preferred) in a quantitative discipline (e.g., Computer Science, Engineering, Mathematics, Statistics).
  • Strong coding skills in SQL and Python.
  • Experience with the machine learning ecosystem, including libraries like pandas, NumPy, and scikit-learn.
  • Proven ability to manage and manipulate large, complex datasets.
  • A detail-oriented, data-driven individual with exceptional problem-solving and storytelling skills.
  • Ability to work independently and collaboratively within a team setting.
  • Excellent time management skills, with the ability to prioritize tasks and meet deadlines with minimal supervision.
  • Note: Candidates must be located in the continental U.S.

Compensation and Benefits

The annual base salary for this role is competitive and based on experience, skills, and education. Additional benefits include comprehensive medical, dental, and vision coverage, a 401(k) plan with company matching, and various wellness programs.

ID Inc. is committed to maintaining a workplace free from discrimination, ensuring that all employees are treated with dignity and respect. We uphold equal employment opportunities and provide reasonable accommodations for qualified individuals with disabilities.

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