Remote Senior Data Scientist

Logo of Oportun

Oportun

📍Remote - Mexico

Job highlights

Summary

Join Oportun's team of mission-driven Data Scientists and contribute to broadening financial inclusion by untapping insights from non-traditional data. As a key member, you will develop and enhance Oportun’s core intellectual property used in scoring risk for underbanked consumers.

Requirements

  • A relentless problem solver and out of the box thinker with a proven track record of driving business results in a timely manner
  • Master’s degree or PhD in Statistics, Mathematics, Computer Science, Engineering or Economics or other quantitative discipline (Bachelor’s degree with significant relevant experience will be considered)
  • Hands on experience leveraging machine learning techniques such as Gradient Boosting, Logistic Regression and Neural Network to solve real world problems
  • 3+ years of hands-on experience with data extraction, cleaning, analysis and building reusable data pipelines; Proficient in SQL, Spark SQL and/or Hive
  • 3+ years of experience in leveraging modern machine learning toolset and programming languages such as Python
  • Excellent written and oral communication skills
  • Strong stakeholder management and project management skills
  • Comfortable in a high-growth, fast-paced, agile environment

Responsibilities

  • Develop data products and machine learning models used in Risk, Fraud, Collections, and portfolio management
  • Build accurate and automated monitoring tools which can help us to keep a close eye on the performance of the models and rules
  • Build model deployment platform which can shorten the time of implementing new models
  • Build end-to-end reusable pipelines from data acquisition to model output delivery
  • Lead initiatives to drive business value from start to finish including project planning, communication, and stakeholder management
  • Lead discussions with Compliance, Bank Partners, and Model Risk Management teams to facilitate the Model Governance Activities such as Model Validations and Monitoring

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