Job Description Your Mission You will be part of a joint team of machine learning engineers and data scientists building and evolving ML models, real-time systems, reports, and deep analysis of fraud detection and mitigation activities to protect merchants, their customers, and Teya from illicit activities.
Working with advanced predictive models and scalable software systems, build and grow intelligent solutions to reduce all kinds of risk and allow Teya to focus on effectively serving our merchants.
In this role, you'll be: Helping Teya to use data to drive business decisions Working on projects including but not limited to fraud detection, transaction monitoring, customer onboarding risk, cost-to-serve and cost-to-acquire modelling Building predictive models to a production level adopting coding best practices Working closely with other data scientists and machine learning engineers to support the analytical part of the machine learning lifecycle Qualifications Your Story Background in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Economics or equivalent) 3+ years of professional working experience Someone who thrives in developing innovative, state-of-the-art products that can meet and surpass the latest advances in the field Proficiency in Python, Amazon SageMaker, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference.
Understanding of ETL processes and data pipelines and ability to work closely with Machine Learning Engineers for product implementation Ability to communicate outcomes of a data analysis to business stakeholders Strong analytical and problem-solving skills Ability to think creatively and insightfully about business problems Nice to have : Proficiency in Snowflake.
Additional Information The Perks We trust you, so we offer flexible working hours, as long it suits both you and your team; Health Insurance; Meal Allowance; 25 days of Annual leave (+ Bank holidays); Public Transportation Card; Frequent team events & activities in the office and outside; Office snacks every day; Friendly, comfortable and informal office environment.