Hydrology Data Scientist
Riverkin
About the Role
Riverkin is a VC-backed Swiss startup looking for a star hydrologist to join the team. Flash floods threaten thousands of people and cause millions in damage each year but trustworthy alerts are not possible to come by. This is a real, under-served problem where today's forecasts break down, leaving first responders and municipalities exposed.What You'll DoBuild the first flash flood ML model
- Define and build the first version of the flash flood ML model, using sensor data we deploy ourselves and public data sources.
- You implement models, manage big data sets and monitor performance.
- You work with software engineer(s) to embed models into a scalable piece of software.
- You are the architect and choose the models, the sensors, and the architecture as we go. Translate Business and Customer Needs into a Technical Roadmap
- You'll partner directly with the founders to pull detailed needs out of clients and find the sweet spot between those needs and technical feasibility.
- You keep track of new developments in nowcasting and flood forecasting tools and techniques and own an ambitious technical vision
- You find the balance between scalable and pragmatic solutions, serving customers from day 1 while working towards a long term strategy.Represent the team on all fronts
- You're comfortable doing a sensor install on a Tuesday and a customer pitch on a Wednesday.
- You are supportive within the team, while standing up for what you believe is best for the customer or company strategy.
- You are an opinionated contributor to key strategic decisions in the company.Create Clarity and Momentum
- Bring structure to ambiguous problems and drive them to execution.
- Make decisions and move forward without waiting for perfect information.Who You Are
- You're excited to solve flash flooding at the local scale
- You want to build a company and you're hungry to act like a founder from day one
- You want to have skin in the game
- You enjoy being a hands-on
- Can take messy inputs and turn them into clear technical direction
- Can move fast, but with enough structure to avoid future pain
- Care deeply about building something that actually works in the real world
- An excellent communicator, with strong written and verbal skillsTechnical Requirements
- Strong experience applying ML tools (e.g. LSTM) to hydrological problems (e.g. flooding)
- Experience in bias correction of weather radar
- MSc or PhD in hydrology, water resources management, atmospheric sciences, or equivalent
- Experience working with real-world data systems (gauges, GIS, satellite imagery, etc.)Nice to Have
- Previous founder or early startup experienceRole Details
- Commitment: 100% FTE.
- Compensation: Commensurate with experience + equity
- Growth: this is a key early hire with the opportunity to build and lead Riverkin’s flash-flood modelling function.
- Location: 4 days per week in Zurich office About Riverkin
We are a well-capitalized startup building real-time sensing and data infrastructure for rivers. Our own field-deployed sensors collect live water-level and sediment data, while our platform turns that data into decision-ready insights for customers. We work across two core use cases: hydropower, where better sediment data can support flushing, asset protection and compliance; and flash-flood risk, where local river data can help first responders and municipalities understand what is happening before conditions become critical. We are a small, hands-on Swiss startup working across hydrology, hardware, field engineering, software and market development.
Riverkin is a VC-backed Swiss startup looking for a star hydrologist to join the team. Flash floods threaten thousands of people and cause millions in damage each year but trustworthy alerts are not possible to come by. This is a real, under-served problem where today's forecasts break down, leaving first responders and municipalities exposed.What You'll DoBuild the first flash flood ML model
- Define and build the first version of the flash flood ML model, using sensor data we deploy ourselves and public data sources.
- You implement models, manage big data sets and monitor performance.
- You work with software engineer(s) to embed models into a scalable piece of software.
- You are the architect and choose the models, the sensors, and the architecture as we go. Translate Business and Customer Needs into a Technical Roadmap
- You'll partner directly with the founders to pull detailed needs out of clients and find the sweet spot between those needs and technical feasibility.
- You keep track of new developments in nowcasting and flood forecasting tools and techniques and own an ambitious technical vision
- You find the balance between scalable and pragmatic solutions, serving customers from day 1 while working towards a long term strategy.Represent the team on all fronts
- You're comfortable doing a sensor install on a Tuesday and a customer pitch on a Wednesday.
- You are supportive within the team, while standing up for what you believe is best for the customer or company strategy.
- You are an opinionated contributor to key strategic decisions in the company.Create Clarity and Momentum
- Bring structure to ambiguous problems and drive them to execution.
- Make decisions and move forward without waiting for perfect information.Who You Are
- You're excited to solve flash flooding at the local scale
- You want to build a company and you're hungry to act like a founder from day one
- You want to have skin in the game
- You enjoy being a hands-on
- Can take messy inputs and turn them into clear technical direction
- Can move fast, but with enough structure to avoid future pain
- Care deeply about building something that actually works in the real world
- An excellent communicator, with strong written and verbal skillsTechnical Requirements
- Strong experience applying ML tools (e.g. LSTM) to hydrological problems (e.g. flooding)
- Experience in bias correction of weather radar
- MSc or PhD in hydrology, water resources management, atmospheric sciences, or equivalent
- Experience working with real-world data systems (gauges, GIS, satellite imagery, etc.)Nice to Have
- Previous founder or early startup experienceRole Details
- Commitment: 100% FTE.
- Compensation: Commensurate with experience + equity
- Growth: this is a key early hire with the opportunity to build and lead Riverkin’s flash-flood modelling function.
- Location: 4 days per week in Zurich office About Riverkin
We are a well-capitalized startup building real-time sensing and data infrastructure for rivers. Our own field-deployed sensors collect live water-level and sediment data, while our platform turns that data into decision-ready insights for customers. We work across two core use cases: hydropower, where better sediment data can support flushing, asset protection and compliance; and flash-flood risk, where local river data can help first responders and municipalities understand what is happening before conditions become critical. We are a small, hands-on Swiss startup working across hydrology, hardware, field engineering, software and market development.
To apply email a brief motivation and CV to E-Mail auf startupticker.ch ansehen
Project description
At Riverkin, we are transforming water management with our innovative Water Data Ecosystem (WDE). We are a well-capitalised startup dedicated to tackling one of the planet’s most urgent challenges: sustainable water management. Our mission is enriched by a team that brings diverse perspectives to the forefront of innovation. Role Overview: you will lead the entire engineering roadmap, from refining Smart Sensors to scaling production for global deployment. This leadership role will have you shaping our technology, our engineering strategies, and our team dynamics. You will work closely with the founders, driving our technology into industries ranging from hydropower to tech. We encourage a culture of balance, collaboration, and open communication, fostering an environment where innovation thrives with every voice heard.Die Stellenanzeige wurde vor Vor 4 Tagen veröffentlicht
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