Your Mission
You will be part of a joint team of machine learning engineers and data scientists building and evolving ML models realtime 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 youll 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 costtoserve and costtoacquire 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 stateoftheart 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 problemsolving skills
- Ability to think creatively and insightfully about business problems
- Nice to have:
- Proficiency in Snowflake.
Additional Information :
The Perks
- Competitive salary;
- Health Insurance;
- 25 days of Annual leave ( Bank holidays);
- Office snacks every day;
- Friendly comfortable and informal office environment;
- Flexible working hours as long it suits both you and your team.
Remote Work :
No
Employment Type :
Fulltime