Data Scientist
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Do you enjoy solving real world problems using data? In Saxo Bank we are on a journey to be data driven in everything we do. We are looking for a Data Engineer/Scientist who wants to embark on the journey.
A key part of Saxo Bank’s success has been our ability to use all available data to deliver best possible products and services. We are looking for a person to help develop our existing and future predictive models focusing on a wide range of areas like marketing, client experience, financial forecasts, and sales.
Predictive Modelling and Client Research
As our new Data Scientist/Engineer you will be part of to the Client Modelling & Digital Analytics w. a current size of 10. The team is part of the Business Development umbrella spanning a diverse set of backgrounds and skills. We touch on the whole business and run projects end-to-end.
You will collaborate with data scientists and data engineers to build data pipelines using Airflow and Databricks, publish data to Kafka and Delta Lake, and write and deploy machine learning APIs to Kubernetes, largely using Python through Databricks.
We are in general NOT looking for someone to spend all day tuning neural networks nor implementing custom AI algorithms. Furthermore, our primary focus is modelling client behavior and not creating trading algorithms.
We are however looking for someone who can write testable production-grade machine learning code, expand our MLOps infrastructure (e.g., CI/CD) for quickly developing new machine learning models and deploying them to production in a scalable and maintainable manner.
As an example, our team recently developed a machine learning model to help determine similarities between stocks. This model has been inserted into our platform and can be seen by our nearly by 1M clients, showcasing the real impact of our projects on the business.
Below are examples of what you can be responsible for:
- Create solid data flows and training-data together with other data scientists using python, Apache Airflow, MLflow, Databricks (PySpark).
- Help in creating, implementing, and maintaining models throughout their life cycle. Including pre- analysis of data, creating the pipelines, looking at performance and setting up surveillance + data quality checks.
- Assist in the development of the data foundation and modelling for our web-analytics and online experience. Includes obtaining an understanding of our current framework and its possibilities.
- Exploring Azure cognitive services and helping to expose the advanced tools to the broader organization.
- Support marketing and the commercial parts of our business on technical questions and solutions related to client/online data.
Your profile
Your colleagues and friends describe you as methodical, curious, self-motivated and with a logical mindset.
We expect you to be comfortable in python and it is preferred to have experience in this domain. We are looking for someone with:
- Relevant education or professional experience in Science, Technology, Economics, or Mathematics.
- Verbal and written English.
The rest of the list below are skills you can learn with us or develop further:
- Experience in Python/PySpark.
- Knowledge of database systems: Efficient in SQL (knowledge of Azure Data Lake, Databricks Delta Lake is a plus).
- ETL skills (knowledge of Apache Airflow, Spark/Databricks, and Kafka).
- Experience with Git.
- Ability to present data in an understandable way (knowledge of PowerBI or similar is a plus).
- A basic mathematical foundation and some statistical/ML knowledge.
We offer:
The COO organisation is responsible for building, constantly developing and improving the full digital value chain that we deliver to our clients and partners. This is done in close collaboration with the Saxo Experience Office and supports the bank in always providing a world-class digital Saxo experience in an efficient, stable and scalable way.
At Saxo IT and the business are integrated, ensuring end-to-end ownership. We are organized based on what we want to do for our clients rather than on subject matter expertise. Within COO you will work together with people from different disciplines, but all with the same goal in mind: making a positive difference for our clients.
The COO umbrella includes the following departments: Operations, Security & Financial Crime Prevention, Trading and our ‘Backbone’ consisting of Enterprise Architecture, Infrastructure, Data Platforms, Workplace Service Management, DevOps Lifecycle Management and IT Business Management.
We aspire to be a non-hierarchical, purpose-driven organisation. At Saxo, it is not about entitlement; it is about impact – no matter where you sit in the organisation. A good idea is always taken seriously and you can truly make a difference.
When you work here, you become a Saxonian. Obviously you will get an attractive compensation package. But we also invest in your personal development and offer you large responsibility from day one. We encourage an open feedback culture and a supportive team environment. If you show a collaborative spirit, drive and passion, your learning curve will be steep and your (international) career opportunities with Saxo immense.
At Saxo we don’t just offer a job – we offer an opportunity to invest in your future!
How to apply:
Click the Apply button to create an account and upload your resume (and a short motivation). We look forward to getting to know you better!
Information og data
Denne ledige stilling har jobtypen "Data Manager", og befinder sig i kategorien "Informationsteknologi".
Arbejdsstedet er beliggende i København
Jobbet er oprettet på vores service den 18.8.2023, men kan have været deaktiveret og genaktiveret igen.
- Data Manager
- København
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Statistik over udbudte jobs som data managere i København
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Statistik over udbudte data managere i København over tid
| Dato | Alle jobs som data managere |
|---|---|
| 25. januar 2025 | 51 |
| 24. januar 2025 | 50 |
| 23. januar 2025 | 47 |
| 22. januar 2025 | 48 |
| 21. januar 2025 | 48 |
| 20. januar 2025 | 49 |
| 19. januar 2025 | 46 |
| 18. januar 2025 | 46 |
| 17. januar 2025 | 49 |
| 16. januar 2025 | 53 |
| 15. januar 2025 | 53 |
| 14. januar 2025 | 52 |
| 13. januar 2025 | 50 |
| 12. januar 2025 | 53 |
| 11. januar 2025 | 52 |
| 10. januar 2025 | 53 |
| 9. januar 2025 | 56 |
| 8. januar 2025 | 57 |
| 7. januar 2025 | 58 |
| 6. januar 2025 | 65 |
| 5. januar 2025 | 68 |
| 4. januar 2025 | 67 |
| 3. januar 2025 | 68 |
| 2. januar 2025 | 68 |
| 1. januar 2025 | 66 |
| 31. december 2024 | 70 |
| 30. december 2024 | 68 |
| 29. december 2024 | 69 |
| 28. december 2024 | 67 |
| 27. december 2024 | 69 |
| 26. december 2024 | 69 |
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