Feedzai

Senior Data Scientist

Feedzaihá mais de um mês

Descrição

Feedzai is building a world of safer money by using trusted AI to detect and prevent financial crime, fraud, and money laundering at scale. The Data Science Team within Customer Success is highly engaged with clients, activating, maintaining, and supporting them while developing models and rules. You will be on the frontline of fighting crime and protecting people from financial harm.

In your day-to-day role, you will understand and clean client data, validate its correctness, and preprocess it using shell scripts and programming languages such as Python, Java, or Scala. You will iteratively compute features and tune parameters to improve model quality, communicate findings to project managers, and work with key stakeholders including data scientists, engineers, and risk managers from our clients. You will also collaborate cross-functionally with Product, Research, and other departments to improve processes, best practices, and tooling.

You will have an MSc or PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, or a related field, with proficiency in Machine Learning, Big Data technologies like Spark and Hadoop, and programming languages including bash, Python, and either Java or Scala. Knowledge of statistics, data visualization, tree-based algorithms, and Deep Learning is a plus. You should have the ability to communicate your findings clearly and work effectively with cross-functional teams in a collaborative environment.

Competências

  • Machine Learning
  • Spark
  • Hadoop
  • Python
  • Java
  • Scala
  • Bash
  • Data Cleaning
  • Feature Engineering
  • Model Tuning
  • Statistics
  • Data Visualization
  • Random Forests
  • XGBoost
  • LGBM
  • Deep Learning

Responsabilidades

  • Understanding the data which clients provide
  • Cleaning and validating data correctness
  • Preprocessing data using shell scripts and programming languages
  • Iteratively computing features and tuning parameters to improve model quality
  • Communicating findings to project managers and assisting in decision making
  • Working with key stakeholders from clients including data scientists, engineers, and risk managers
  • Collaborating with Product, Research, and other departments to improve processes and tooling

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