Do you want to be part of the data science journey in one of the largest financial institutions in Northern Europe? Are you committed and able to apply your extensive analytical skills? Can you create value for Danske Bank customers by detecting financial crime through advanced machine learning?

Join 1st Line Financial Crime Machine Learning Team, a team of experts within different areas of expertise, responsible for ensuring an agile ever-growing detection setup. We are currently looking for an experienced data scientist to assist expand our data science competencies in financial crime modelling, and you have the possibility to contribute.

We are looking for people with a genuine interest in researching and applying state-of-the-art generative machine learning methods. This will likely be demonstrated via a strong academic publication track record or GitHub repo. We offer you an opportunity to continue learning through interactions with colleagues, a weekly journal club and a dedicated time and monetary budget.

The team is located in Copenhagen and Vilnius – you will be based in Vilnius and be part of a professional, Nordic environment with a significant focus on performance, academic insights and emphasis on delivering results.

Depending on your experience and knowledge we may offer you a different seniority of the role.

• Be working with data analysis and development of probabilistic machine learning models for our financial crime solutions
• Continuously improve and innovate new and existing models through Bayesian predictive modelling or generative modelling techniques
• Be applying your theoretical insights and practical experience to solve real problems
• Be working hands-on and will take part in all aspects of developing and maintaining supervised and unsupervised modelling of financial crime
• Have close collaboration with experts across business and IT to bring the best solutions to life in your daily work

• Proven experience in handling large amounts of data and fluency in Python/R, SQL, PySpark, etc.
• Ideally, hold a PhD degree within a quantitative field and have experience in data analysis, data cleaning, feature engineering and development of machine learning models (concepts like eigenvalues, inner joins, posterior distributions, and sigmoids should not be new to you)
• Have a clear vision of future developments in predictive and generative modelling
• Can combine solid business understanding and commercial awareness with experience within scripting languages and extraction of structured, semi-structured and unstructured data
• Have an analytical mindset and a fact-based approach, and you understand the need for applying data as a competitive advantage in the banking environment
• Result-oriented and with a positive mindset and a proactive attitude
• As you will join an international environment, advanced English skills are key
• Experience in financial services would be considered as a pro but not a requirement
• Advanced English skills

Monthly salary range from 2960 EUR to 4440 EUR gross (based on your competencies relevant for the job).

Additionally, each Danske Bank employee receives employee benefits package which includes:

• Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.
• Health & Well-being: a diverse, inclusive, work & life balance work environment; health insurance from the first day of employment; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.
• Hybrid working conditions: home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.
• Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.
• Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.

• Canteen services and free fruits
• 24/7 gym services and group trainings
• Health insurance from the first day of employment
• Third pillar pension fund