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.
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.
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.
Why Sense
Join Sense and be part of our mission to reduce global carbon emissions by making homes smart and more efficient. Our energy data and tools demystify home energy use, empower people to take command of their usage, and enable utilities to build a cleaner and more resilient grid.
Sense supports a diverse and inclusive workplace where we all learn from each other. We welcome candidates with backgrounds that are traditionally underrepresented in tech, and we strive to foster an engaging, respectful and supportive community where everyone feels empowered to do their best work. Sense is committed to be an equal opportunity employer.
Be a part of building something that will make a difference in the world.
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