Medior Data Scientist at Ing Firm

, , Netherlands -

Full Time

Start Date

Immediate

Expiry Date

22 Apr, 26

Salary

0.0

Posted On

22 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Statistical Modelling, Machine Learning, Financial Crime Prevention, Python Programming, Object-Oriented Programming, Apache Spark, Communication Skills, Mentoring, Team Collaboration, Machine Learning Algorithms, Curiosity, Problem Solving, Data-Driven Solutions, Statistical Knowledge, Software Engineering Practices

Industry

Banking

Description

ING’s goal is to enable people to “do their thing” and empower them to stay a step ahead in life and in business. We are one of the largest banks in Europe and we continuously evolve to become one of the most innovative companies in the banking sector. The ING Analytics group is a major driving force in ING’s transformation, aimed at helping us to become a data-driven organization, where advanced analytics is at the heart of our business processes. The team In our ING Analytics for COO Analytics Tribe within Financial Crime Transaction Monitoring, we are passionate about creating advanced analytics applications to mitigate the risk of financial, economic crimes (FEC) for our society, and about delivering models and products across multiple countries and domains, making ING a safer and more compliant bank. We are a diverse international group which combines data, IT, and product management roles in interdisciplinary squads, and we strive to push the boundaries of utilizing our big and sensitive data sources with statistical and machine learning understanding to tackle important challenges, such as anti-money laundering (AML), counter-terrorist financing (CTF) and post-transaction monitoring (PTM). Roles and responsibilities As part of the team, you will help creating innovative scalable data driven solutions in the space of Financial Crime Transaction Monitoring. You proactively work with multiple teams to implement these solutions across the organization by assuring close alignments on the technical requirements and delivery. You have at least 4 years of (global) work experience in the Data Science space (methods, technology, data) including statistical modelling and machine learning experience to solve business questions and/or develop (innovative) data driven products Experience in applying data science to prevent and detect financial crimes (e.g. internal/external fraud, money laundering, terrorism financing, tax evasion, …) is a strong plus Scikit-learn Professional Practitioner certificate is a plus You have excellent communication skills and you can explain complicated subjects clearly You are friendly and approachable and are able to mentor junior data scientists You are capable of working collaboratively in a semi-remote, globally distributed team. Your enthusiasm is visible and you are good with mobilizing people for our data driven purpose You are motivated to keep on top of the latest developments You have extensive knowledge of a wide range of machine learning algorithms, ranging from more classical econometric models to cutting-edge neural networks and are able to match them to business problems You are able to see where ING can set further steps towards becoming a truly data driven bank. You’re always thinking one step ahead, for example in advising about the best way of implementation. You are a team player who strikes effective balance between independence and acting in the interest of the team How to succeed We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself. MSc or PhD with excellent academic results in the field of Data Science, Computer Science, Mathematics, Physics, Engineering, Econometrics or similar.M You have a profound theoretical understanding of Machine Learning: Classification, Outlier detection, NLP, Regression, Clustering etc. You have extensive experience with algorithms like Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc. Knowledge of parametric and non-parametric statistics is a strong plus. Strong Python programming skills, including object-oriented programming, package development, working with Git. Familiarity with software engineering practices is a plus. Experience with Apache Spark Rewards and benefits We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions. The benefits of working with us at ING include: 25-28 vacation days depending on contract Pension scheme 13th month salary 8% Holiday payment Hybrid working Personal growth and challenging work with endless possibilities An informal working environment with innovative colleagues About us Curious about how ING empowers people and businesses to move forward? Discover what we do and what we can offer you. Questions? Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button. We hire people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on more responsibility. In return, we’ll back you to develop into an even more awesome version of yourself. With around 57,000 employees in over 40 countries, there is no shortage of opportunities. Show us initiative and we’ll let you make a difference. ING is a great place to join. We work in a highly dynamic environment where people are trusted to make decisions and every voice gets heard. If you have an idea how to make things better, you’ll be encouraged to make it happen – regardless of your position. We’d love to meet you.

Responsibilities

You will help create innovative scalable data-driven solutions in Financial Crime Transaction Monitoring. You will work with multiple teams to implement these solutions while ensuring alignment on technical requirements and delivery.