Teya

Data Scientist – Fraud and Risk Evaluation

28 October 2024
Full Time
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Deadline date:
£77000 - £143000 / year

Job Description

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.

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