About this job
Sr Data Scientist | Hybrid | Berlin | €70-90k | GreenTec
I am partnered with a client based in Berlin looking to expand their ML team and I am searching for a talented Machine Learning Engineer with expertise in remote sensing to join their team in
Berlin (flexible Hybrid work arrangements possible). In this role, you will play a key part in developing and deploying machine learning models that extract valuable information from satellite
imagery and other remote sensing data sources. 3-4 stage interview process.
Responsibilities:
- Design, develop, and implement: machine learning models for tasks such as object detection, classification, and time series analysis of remote sensing data.
- Develop smoke detection models: Analyze sensor data to identify early signs of fire using your machine learning expertise (think deep learning!).
- Deploy and test sensors: Get your hands dirty! You’ll help us deploy and experiment with sensor networks in real forests.
- Build the data pipeline: Streamline the flow of data from sensors to our AI models using ETL pipelines (think data hero!).
- Predict forest health: Develop models to predict forest health based on climate change, empowering owners and authorities to take action.
- Become a fire prediction Expert: Build or use existing models to predict wildfires and supplement our sensor-based approach.
Qualifications:
- Holds a Master’s or PhD in Data Science, Statistics, CS, Math, or a similar field.
- Has 5 years of data science experience (you know your stuff!).
- Has expertise in machine learning and experience with TensorFlow, PyTorch, and scikit-learn.
- Experienced time series forecasting, division trees, XGBoost, and ensemble techniques.
- Can tame complex data with PCA, T-SNE, and k-means clustering.
- Has experience with ETL pipelines and MLflow (end-to-end ML pipelines are your jam).
- Can communicate clearly and present your findings with confidence.
- Thrives in a team environment and enjoys independent work.
- Can translate complex technical concepts and understand requirements.
Benefits:
- Competitive salary and benefits package.
- Opportunity to work on challenging and impactful projects.
- Collaborative and supportive work environment.
- Flexible work arrangements (remote work possible).
- Continuous learning and development opportunities.
Please apply with your CV, email and contact number. Or alternatively reach out to me on LinkedIn