Data Scientist

  • Paysafe
  • Irvine, CA, United States
  • Jul 28, 2017
Full time Risk

Job Description

The Data Scientist in the Risk Management team will be responsible for conceptualizing and developing data-driven risk solutions by applying advanced analytical techniques. The Data Scientist will play an integral role by developing rules and models to effectively detect risk within the overall portfolio, and building systems to scale our business in an efficient manner as well as developing our long-term roadmap for effective risk and fraud management.

 

The Data Scientist is expected to thoroughly understand the payments risk domain, and also frequently interact with risk analysts in the team to understand the emerging trends in merchant risk profiles and translate those findings into tangible solutions. The candidate will support overall risk goals through detailed data analysis that results in policies, programs, and broad strategies to deliver a world-class risk management experience to our merchants. The candidate is expected to do root-cause analysis of directional change in KPIs and provide analytical support to the operational teams, assisting in the development and automation of ongoing reports necessary to monitor and track the performance goals of our risk management teams (Risk Monitoring, Credit Underwriting, and Compliance). 

 

 

Core Responsibilities include:

 

  • Actively manage programs and strategies for effective detection of credit and fraud risk within the overall merchant portfolio
  • Build advanced analytical models /data mining algorithms such as Multivariate Regression, Logistic Regression, clustering algorithms, Support Vector Machines, Decision Trees, etc.
  • Partner with cross functional teams of risk analysts, analytical and product development resources to identify and promote new solutions and products that will improve the overall effectiveness of merchant risk monitoring and risk programs.
  • Produce forecasting models, analysis, and recommendations to understand and mitigate risk and protect against potential vulnerabilities
  • Perform root–cause analysis to significant changes in KPIs
  • Perform in-depth data analysis on risk profiles of existing merchant accounts and prior losses to identify new actionable trends
  • Prepare and extract data from databases. Analyze hundreds of variables covering a wide range of information from user profile to historical transaction data. Identify emerging risk patterns and create new variables pertaining to these.
  • Work with technology teams to develop and implement analytical solutions in a production environment
  • Perform ad hoc data analysis requests and other related assignments/projects as requested by management

 

Skills & Experience:

 

  • Bachelor’s degree, preferably in statistics, engineering, computer science or any other quantitative discipline. Master’s degree preferred
  • 3+ years of experience, preferably in a data science role.
  • Strong problem solving skills and communication skills
  • Background in data mining, machine learning, statistical analysis, and modeling, with experience deploying models in a production environment
  • Statistical computing in at least one scripting language such as R, Python.
  • Proven ability to independently deliver end-to-end analytic solutions by asking the right questions, identifying necessary data sources, building predictive models, and producing actionable results
  • Experience with supervised and unsupervised machine learning theory and practice is preferred
  • Strong knowledge of database querying and data analysis using SQL, SSRS and other tools
  • Familiarity with card acquiring industry and credit risk is preferred
  • Preferably live within the Orange County area. This role does not qualify for relocation assistance
  • Can communicate clearly, both written and verbally