Financiële diensten
Data Scientist (MLOps, time-series modeling for recurring patterns)
Vandaag toegevoegd
Via verloning
Croeselaan 18, Utrecht
36 uur per week
30 jul 2027
Deadline: 1 uur geleden
Sommige details van deze opdracht zijn niet publiek beschikbaar.
Word gratis lidOver de opdracht
A Data Scientist works in a team focused on enriching transaction data by detecting recurring periodic patterns. The assignment centers on improving model performance, automating processes, and optimizing algorithms to support better financial insights. The role is performed in an end-to-end environment with Data Scientists and ML engineers, supported by a business analyst, scrum master, and product management.
Role and responsibilities
- Shape the future of the model through model design, high-quality code, and alignment with adjacent disciplines such as IT, architecture, and business.
- Improve the performance of the periodicity detection model.
- Own the full MLOps live cycle from deployment to ongoing operation.
- Extend the model’s time-related feature set to increase predictive value.
- Contribute to production code delivery within the team.
- Introduce and discuss innovative analytics ideas based on an understanding of the broader analytics landscape.
Practical examples
Work follows a hybrid approach with regular office days and additional flexible presence. The assignment is limited in duration and is based in an office in the Netherlands.
Eisen
- Language: English mandatory
- ZZP Allowed: NO
- 1 FTE
- Duration: 12 months
- Preferred working hours: 36 hours, minimum 32 hours
- Experience: 5+ years of work experience; experience with Git is a must
- Academic degree (MSc / Phd) in Data Science, Econometrics, Mathematics or a related field
- 5+ years experience in advanced analytics / modelling / artificial intelligence activities (ideally with large data sets)
- Experience with Python, PySpark and Git
- Excellent verbal and written communication skills in English
Wensen
- Experience with Python, PySpark and Git (Azure Databricks experience is a plus)
- Time series and predictions experience is a plus
Uurtarief overzicht
Klantbudget (onbekend)100%
WorkNew marge−5%
Werkgeverskosten−10%
Budget voor jou
85%