Data Scientist • Mid • Full-time
Data Scientist (Product-oriented)
Dryp builds IoT- and data-driven technology that helps utilities and cities prevent flooding and reduce environmental impact from wastewater and stormwater systems. We combine advanced sensor networks, hydrological modelling, and cloud software to enable real-time operational decision-making for utilities across the Nordics. As we scale our product and expand our capabilities, we are now strengthening our data science and ML foundation. We are looking for a Product-oriented Data Scientist to help shape the next generation of automated insights in our platform Lens.
The Role
You will play a key role in turning complex, real-world data into actionable insights for our customers. This is a highly product-facing role where you will work closely with product, hydrologists, backend engineers, and frontend developers.
You will
- Drive the development of next-generation automated insights in Lens
- Translate complex data streams (sensors, rainfall, SCADA, GIS) into actionable outputs for operational decision-making
- Build and improve models for forecasting, event detection, and smart gap filling in time series data
- Define the concept of “minimum viable truth” in data: when is data good enough to support decisions?
- Contribute to automating data cleaning, validation, and quality assurance processes
- Experiment with AI/ML approaches to scale insights across customers and networks
- Translate domain knowledge from hydraulics and wastewater systems into scalable models and features
Who You Are
We’re looking for someone who thrives at the intersection of data science, product thinking, and real-world physical systems.
You will likely recognize yourself in this
- You take initiative and enjoy turning open-ended problems into concrete models and solutions
- You are curious about the domain and motivated by understanding how water systems behave in the real world
- You have an eye for disseminating and presenting model results to actionable insights for users (in cooperation with UI/UX colleagues)
- You are strong in working with noisy, imperfect, and incomplete datasets
- You think beyond models and care about how they create real product value
- You enjoy collaborating with both technical and non-technical stakeholders
Experience That Matters
Must-haves
- Solid experience in applied data science / machine learning in a product and operational environment
- Strong Python skills and experience working with time series data and databases
- Experience handling noisy, real-world sensor or operational data
- Ability to bring data science work into production and turn it into product features
- Experience from startup/scale-up or similarly fast-paced environments
Nice-to-haves
- Experience with forecasting, anomaly detection, or event detection in time series
- Familiarity with streaming data or event-driven architectures
- Interest or experience in hydraulics, fluid dynamics, rainfall, or physical modelling
- Experience with cloud platforms (AWS) and deploying ML systems on scalable infrastructure
- Knowledge of data pipelines and data quality frameworks
How to apply
Send your application and CV to cecilie@drypdata.com - we conduct interviews on an ongoing basis and aim to hire as soon as possible.
