Posted about 7 days

Data Engineer w/ Machine Learning

Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex, high volume data from a variety of sources. Analyzes large quantities of data and presents insights and predictions (e.g., on client behaviors and preferences, new products and services) to support management planning, execution and monitoring of business decisions, specially focused on Fraud prevention through the use of Machine Learning; Builds and maintains the production execution of Data Science into enterprise systems and architecture.


• Manipulate data to perform analysis, including querying data, defining metrics, or analyzing data to evaluate a hypothesis. 

• Manage machine learning model life cycle through model audit, back testing, forward testing, benchmarking with the help of performance metrics. 

• Build machine learning/deep learning models that detect risk activity 

• Conduct exploratory data analysis, supervised, unsupervised and semi-supervised machine learning to identify fraud trend, segment and clusters, and optimization opportunity. 

• Researching and evaluating new model architectures which improve the accuracy of our prediction models. 

• Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria. 

• Cooperate with cross-functional teams across the organization in finding insights and developing the right data solutions. 

• Collaborating with our data science team for statistical analysis on which machine learning approach to use, including the modeling of the algorithm and prototype for testing.



• Bachelor's degree required, Master's degree preferred in Software Engineering, Computer Science; or equivalent work experience in a Technology or business environment. 

• Minimum of 7 years experience working in software development, design, business intelligence environments, and / or data architecture environments.

 • Minimum of 3 years experience working in applied Machine learning or Deep learning.

 • Full proficiency with multiple programming languages and / or database management and modelling. 

• Excellent verbal and written communication skills.

 • Highly proficient in leading large scale projects or significant project steps and communicating progress/approach with technical/non-technical peers/clients and leaders.

 • Proficiency in payment systems and the merchant acquiring business is an asset.

  • 1 Interview 30'
  • 2 Interview with the final Client 60'