Our client is one of the most frequently used mobile platforms globally. their mobile application has been downloaded onto over 75 million mobile devices, as a service for on-demand transportation and mobile payments platform. They have effectively raised over US $2 billion in the last round of funding. They have experience 3x growth year over year and in the process of building out their Research and Engineering team in Seattle.
Manage and own the entire end-to-end lifecycle of designing models, working with Engineering for implementation, to maintenance and enforcement.
Generate multivariate statistical models to identify latent factors, preventive and preemptive capabilities that the trust framework requires.
Interface with business & operation teams to formulate solutions & product changes informed by your findings.
Work independently or in a team to solve complex problem statements.
Design and implement RESTful APIs.
Design and implement single page applications (ReactJS, Redux, Webpack, GulpJS).
Architect efficient and scalable backend systems.
Write unit, functional and end-to-end tests.
Write high-quality code (Go) that communicates with upstream backend services via HTTP API's.
Deep understanding of the fraud space with hands-on knowledge of fraud, payments and risk, especially on tech products.
Experience in geospatial databases or graph databases.
Recent programming experience in a production environment.
Experience in Scala or PySpark on distributed systems.
Interest in working with MapReduce technologies (such as Hadoop / Spark).
Familiarity with Python Scikit Learn, Panda or Spark ML/Mllib is a plus.
Proficient in RDBMS such as PostgresQL or MySQL; and statistical programming in languages like R, Python, Java, C++ or SAS
Experience in ETL, feature selections, modeling, model validation and conducting data analyses using R, SQL, Python or any JVM languages
Deep understanding and implementation experience of predictive modeling algorithms such as logistic regression, neural networks, forward propagation, decision trees and heuristic models, with familiarity dealing with trade offs between model performance and business needs.
Experience in interfacing with other teams and departments to deliver impact solutions for organisation.
Self-motivated, independent learner, and enjoy sharing knowledge with team members.
Detail-oriented and efficient time manager in a dynamic and fast-paced working environment.
Bachelors degree in Computer Science. Masters preferred.