Student Data Scientist (NLP)

Are you excited about designing and developing Machine Learning models? Do you have an interest in understanding business problems and find AI solutions to them? Do you have what it takes to increase your power level beyond that of a Notebook Ninja? If so, we want you to join our team as a Student Data Scientist in Commercial Data Science.
Are you excited about designing and developing Machine Learning models? Do you have an interest in understanding business problems and find AI solutions to them? Do you have what it takes to increase your power level beyond that of a Notebook Ninja? If so, we want you to join our team as a Student Data Scientist in Commercial Data Science.
We develop a wide range of models that identify customer needs and how we can aid them using financial services (our so-called Next Best Action engine). Using data from customer interaction (messages, chats and calls) we develop NLP solutions that help provide automatic replies and digital routing to create a better customer experience and lower costs from manual processes.

In this role, an explorative mindset is crucial as you will be tasked with uncovering new insights and opportunities from complex data sets. Furthermore, we have ongoing Generative AI (GenAI) projects and PoCs utilising LLMs and vector stores for Retrieval Augmented Generation Tasks for several purposes across the bank. Danske Bank is currently building a full-scale GenAI unit.

Skills in data visualization will be highly valued, as you will be required to present data in a clear, concise manner to various stakeholders, aiding in the understanding and decision-making process.

Therefore you will be working towards developing and exposing AI and ML software to automate predictive models for recommendation, customer self-service (auto-reply) and GenAI.

Your Challenges
In close collaboration with Data Scientists, Data Engineers and ML Engineers you will be responsible for ensuring that business problems are converted to models and solutions that you and the team can build and deploy. You will engage with team members and business owners to understand end-user needs.

As part of our venture into Generative AI, you will be part of scoping and testing practical use cases to understand the potential for the bank. This will happen in close collaboration with peers in other teams across the organization.

As a Student Data Scientist you will:

• Build and monitor both online and batch models, delivering the model output as data or exposed as API endpoints.
• Utilize off-the-shelf models from e.g. HuggingFace for ML tasks.
• Be a role model to other members of the team and help educate Data Scientists, ML Engineers and Data Engineers in the Data Science discipline to ensure that we leverage all its capabilities.
• Work in an agile framework, prioritizing your backlog to continuously deliver results.
• Cultivate good relationships with data scientists and business experts across the organisation, making their problems yours and providing necessary solutions through products and services.
• Extend existing ML libraries and frameworks.
• Continuously research and analyse the MLOps market, user needs and the product roadmap. Identify potentials for product expansion or pivoting as well as collaborations with external partners, vendors, and open source.

A great match
We imagine that you are in your last year of your Bachelor or in the beginning of your Master education in Computer Science, Data Science or other relevant STEM educations, as well as experience in a similar role. We also imagine that you possess great problem-solving skills, paired with a desire to learn and grow, as the data science landscape changes.

About you
Do you recognise yourself in some of these technologies?

• Fine-tuning and/or tinkering with pretrained transformer models (e.g. from Huggingface)
• Knowledge about Retrieval Augmented Generation
• Familiar with Generative AI technologies including use of GenAI model APIs (e.g. GPT-4, Llama3), embedding models, vector databases, langchain, etc.
• Languages/Tools:
  • Python
  • Spark/PySpark
  • Airflow
  • SQL
  • Public Cloud providers (preferably AWS)
  • Terraform
  • MLFlow
  • Containerisation (ex. Kubernetes, Docker, Openshift)
  • Git/Azure DevOps
• Self-driven with an ability to work individually and with others in the team and organisation
• Outcome-oriented with a focus on delivering
• Curious about product development, technology trends with a thirst for knowledge and self-improvement

About the Department
We are a diverse team of Data Scientists, Data Engineers and ML Engineers with colleagues in both Scandinavia, India and Lithuania. We have a very research-oriented culture and aim at staying up to date through various research projects with university partnerships across the greater Copenhagen area.

As part of the Commercial Data Science Center of Excellence you will be working in our office in Copenhagen and sit in central part of Danske Banks commercial organisation. We support all 4 Nordic countries (Denmark, Sweden, Norway and Finland) with bleeding edge Machine Learning solutions.

We work closely with the development organization to deliver and integrate Machine Learning solutions in our product offering such as the Mobile Bank, eBank, website and frontline advisors.

We aim at creating a good social atmosphere by arranging events such as hackathons, board game nights, team days etc.

Is this the job for you?
The position is typically 15-20 hours per week. We value a mutually flexible approach to working time - both during our busy periods and during your exam periods. We have a working from home setup where most colleagues work from home a few days a week.
If this sounds great to you, then do not hesitate to apply or reach out! We conduct interviews on an ongoing basis and hire when we find the right candidates.

Please feel free to contact if you have any questions:

• Head of Advanced Commercial Analytics, Rasmus Brink, via email [email protected] or LinkedIn.
• NLP Lead Data Scientist, Ledian Selimaj, via email [email protected] or LinkedIn.

Adresse:
Bernstorffsgade 40
1577 København V