Senior Data Scientist.

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