Data Scientist - Deep Learning Focus

About Sense:

At Sense, our mission is to make all homes intelligent by keeping people informed about what's happening in their homes, helping to make them safer, more efficient, and more reliable.

We are committed to making a real impact on climate change by developing cutting-edge AI solutions for energy monitoring and smart home intelligence.

About the Role:

We are looking for a Data scientist with a passion for deep learning and time series analysis to join our team. In this role, you will work on developing and optimizing machine learning models that help detect and analyze energy usage in homes.

This is a great opportunity for someone early in their career to gain hands-on experience with real-world machine learning applications, work with large datasets, and contribute to both cloud and embedded AI deployments.

Responsibilities:

• Assist in designing and training deep learning models for device disaggregation.
• Perform data preprocessing and analysis to prepare datasets for model training.
• Conduct experiments with different model architectures and hyperparameters to optimize performance.
• Help curate ground truth datasets for model evaluation.
• Work with the engineering team to support model deployment in both cloud-based and embedded systems.
• Stay updated on deep learning advancements and contribute to best practices in model development.
• Collaborate with senior data scientists and engineers to improve data science infrastructure.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Machine Learning, Electrical Engineering, or a related field.
• 1 to 3 years of professional experience in data science or machine learning 
• Familiarity with deep learning frameworks like TensorFlow or PyTorch.
• Basic understanding of neural network architectures (CNNs, RNNs, Transformers).
• Proficiency in Python and relevant data science libraries (NumPy, Pandas, Scikit-learn).
• Experience working with large datasets is a plus.
• Strong problem-solving and analytical skills.
• Enthusiasm for learning and growing in a collaborative, fast-paced environment.