The world's forests are burning! If current trends continue, up to 170 million hectares could be lost by 2030 and with it we gradually lose the earth's great carbon sink consuming 110 billion metric tons of CO2. Are you passionate about protecting the planet's most valuable resource and looking for an opportunity to contribute? Do you want to help mitigate the ever growing threat of climate change?
Dryad is an environmental IoT startup based in Berlin-Brandenburg. Our mission is to develop a large-scale IoT network that allows public and private forest owners to monitor, analyze and protect the world’s largest, most remote forests. Our goal is to build and deploy a robust and reliable ultra-early fire detection system to prevent the spread of forest fires as well as a monitoring platform to ensure the health of forests.
To fulfill our mission we are looking for a Senior Data Scientist to join our team in Berlin to work on development of smoke detection models for early fire detection using gas sensors.
Responsibilities:
- Contributing to smoke test experiments with regards to understanding and organization of resulting experiment data.
- Experiment with sensor deployments on-site, also in forests.
- Development of ETL pipeline to streamline the experiment data to AI models process.
- Development of a smoke recognition model based on outputs of several sensor readings; ML experience including deep learning is required
- Development of forest health prediction models taking into consideration climate change and its effect on forest ecosystems to help forest owners and relevant authorities better monitor and manage forests.
- Development / Use of forest fire prediction models to further augment and enhance the sensor based approach.
Required skills, knowledge and experience:
- Master’s or PhD degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
- 5+ years of experience in data science or a related field.
- Proficient in Python.
- Strong experience with machine learning frameworks: TensorFlow, PyTorch, scikit-learn.
- Strong experience with modeling tabular data: Time Series Forecasting, Decision Trees, XGBoost, Ensemble techniques.
- Strong experience with advanced data analysis techniques: PCA, T-SNE, k-means clustering.
- Experience with end-to-end ML pipeline tooling: ETL pipelines, MLflow.
- Excellent communication and presentation skills.
- Ability to work independently and as part of a team.
- Ability to communicate technical concepts and understand technical requirements.
Perks:
- Contribute to protecting the world’s forests and mitigate effects of climate change, make impact!
- Influence the design and development of a cutting edge one-of-its-kind sensor-based forest fire detection system.
- Opportunity to work in a small, experienced team where you're constantly challenged to learn and set the bar higher.
- Competitive compensation.
This is an interesting and challenging role and would suit a confident self-starter, willing to work with others and on their own initiative.
We encourage everyone regardless of age, gender, identity, race, ethnicity, nationality, religion and sexual orientation to apply for this position. We aim to build a diverse team with an inclusive approach.
Please send applications to: hr@dryad.net