Data Scientist (AFC) at N26

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

06 Jan, 26

Salary

0.0

Posted On

08 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Data Science, Machine Learning, SQL, Python, R, Transaction Monitoring, Financial Crime, Regulatory Compliance, Statistical Analysis, Project Management, Stakeholder Engagement, Communication Skills, Collaboration, Analytical Skills, Risk Assessment, Fraud Detection

Industry

Financial Services

Description

About the opportunity Join our international AFC Modelling Team as a Data Scientist for Fincrime and help us combat financial crime. You have a background in regulatory obligations related to Sanction Screening and hands-on experience in analyzing and utilizing data for the development and configuration of analytical financial crime detection models. You thrive in a highly motivated team environment, are self-driven, and are focused on project delivery. Do you have experience with Machine Learning models and a desire to apply them to financial crime detection? You will leverage advanced technologies to address risks associated with Money Laundering, Terrorism Financing, Fraud, and Sanctions. You will collaborate closely with other AFC Modelling teams responsible for identifying and assessing financial crime risks and reviewing your models, as well as with the Data Science team that develops fincrime-specific machine learning models. In this role, you will: Work within a high performance team that is the central point of contact for all anti-financial crime (AFC) modelling tasks, work cross functionally with various teams Be an expert regarding concepts and approaches of post and real-time Transaction Monitoring / Screening models Have technical expertise around SQL, in implementing Transaction Monitoring models (e.g. in python) and around Machine Learning techniques Independently develop new AFC models and tune existing rule based or machine learning models within the Modelling function Review and enhance existing processes within the Modelling function Perform statistical analysis around AFC models for multiple purposes Work closely with the Threat Identification and Model Review Function around model enhancements Lead small projects from conception to completion, including developing project plans, tracking progress, and managing stakeholder communications What you need to be successful: Background A university degree in mathematics, economics, computer science, data science, information management, statistics or other relevant areas Professional experience gained in an anti-financial crime, compliance or risk management role, ideally with at least 3+ years Machine Learning background with a minimum of 1-2 years' experience in applying models to production Skills Knowledge of the regulatory environment and related requirements with regards to topics such as Know Your Customer, financial crime risk assessment, transaction monitoring or screening to mitigate money laundering, fraud, terrorist financing, sanctions risk Strong analytics skills including the knowledge of a query language e.g. SQL Expertise in an analytical programming language like Python or R Fluent in English, strong communication skills Collaborative and results-driven team player Strong project management, presentation and stakeholder engagement skills Nice to haves A professional Financial Crime qualification from an internationally recognised body (e.g. ICA, ACAMS) What’s in it for you: Accelerate your career growth by joining one of Europe’s most talked about disruptors. Employee benefits that range from a competitive personal development budget, work from home budget, discounts to fitness & wellness memberships, language apps and public transportation. Come together with your team in the office for a dedicated day of teamwork each week, plus another day of your choice, and enjoy the flexibility of remote work the rest of the time. Some roles may require additional in-office presence. As an N26 employee you will have access to a Premium subscription on your personal N26 bank account. As well as subscriptions for friends and family members. Additional day of annual leave for each year of service. A high degree of autonomy and access to cutting edge technologies - all while working with a friendly team of peers of diverse nationalities, life experiences and backgrounds. A relocation package with visa support for those who need it. Who we are N26 has reimagined banking for today’s digital world. Technology and design empower everything we do and it’s how we are building the global banking platform the world loves to use. We've eliminated physical branches, paperwork, and hidden fees for an elegant digital experience and supreme savings. Giving people the power to live and bank their way is what gets us out of bed in the morning and inspires the work that we do. We are headquartered in Berlin with offices in multiple cities across Europe, including Vienna and Barcelona, and a 1,500-strong team of more than 80 nationalities. Sounds good? Apply now for this position. Equal Opportunities: We recognize that our strength lies in our people and the varied perspectives they bring to our workforce. We strive to build talented and diverse teams to drive our business success and empower our people to reach their full potential. We genuinely welcome and encourage applications from people of all backgrounds, cultures, genders, sexual orientations, abilities, neurodiversities, and ages. We're committed to creating an inclusive workspace where everyone feels valued and respected, free from harassment and discrimination. If there's anything you need to make the application process work for you, please let us know by reaching out to candidate.exp@n26.com. Visit our website to learn more about Diversity, Equity, & Inclusion at N26.

Responsibilities

As a Data Scientist in the AFC Modelling Team, you will develop and tune analytical models for financial crime detection. You will collaborate with various teams to enhance existing processes and lead small projects from conception to completion.