Senior Data Scientist

About the Role

As a Senior Data Scientist for the Physical Identities team, your primary responsibility will be to design, build, deploy and monitor machine learning models and solutions specifically tailored for our identity verification products. In this role, you will collaborate closely with Product Managers, Data Scientists, Machine Learning Engineers, Software Engineers and other data professionals to develop state-of-the-art document detection and classification, data extraction and fraud detection algorithms. You will drive projects like, document detection and classification, OCR extraction and validation, supervised/unsupervised detection of anomalies in physical documents or document fraud risk scoring systems and leverage our large knowledge base and production data volumes to take these initiatives from initial prototype through full production deployment.

You’ll help us protect honest people online by:

• Owning end-to-end responsibility for building identity verification machine learning models from prototyping to production and driving measurable impact in live environments
• Taking full ownership for performance metrics like verification accuracy and false acceptance rates, and pushing the boundaries of what’s possible under high-security constraints
• Influencing and shaping our in-house models, and evaluating external solution vendors, and improving instrumentation to generate valuable insights while creating new machine learning products
• Establishing key metrics, deriving data-driven insights, and conducting experiments to assess the overall product impact of our biometric machine learning solutions on identity verification
• Working both independently and collaboratively with other engineers to define and deliver high-impact product features in the biometrics domain

You are the right future Veriffian for the job if you have:

• Previous end-to-end professional experience in the identity verification industry, successfully delivering high-performance machine learning models in the verification of physical identity documents.
• Theoretical and applied knowledge in Machine Learning concepts with a special focus on Computer Vision, Data Extraction and Anomaly Detection techniques
• Hands-on experience working with Deep Learning toolkits such as Tensorflow or PyTorch and Gradient Boosted models libraries like XGBoost or Catboost.
• Great product thinking skills.
• Proficiency in SQL
• Can effectively communicate the results and trade-offs to both technical and non-technical audiences
• Enjoy working in a fast-paced, highly fluid, and multi-functional environment.