(H-606) | Data Scientist (Mid And Senior) - Fraud And Risk Evaluation

Detalles de la oferta

Company Description
About Teya
Teya exists to make sure that every small and growing business in Europe has the opportunity to thrive. We want to become Europe's go-to software solution for these businesses, simplifying their every day and helping them reconnect with the joy of running their business. Teya was born in 2019 and is home to over 1,000 employees in 15+ countries. We've built a fast-paced, energetic, and innovative environment that is dedicated to bringing the best solutions to customers.
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
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.
Summary
Type: Full-time
Function: Engineering
Experience level: Mid-Senior Level
Industry: Financial Services

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Salario Nominal: A convenir

Fuente: Jobleads

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