Our mission:

We are on a mission to address climate change by decarbonizing commercial buildings.

Your impact:

At our company, we live and breathe data. As a Senior Data Scientist, you will play a pivotal role in defining our data-driven product development culture. Collaborating closely with engineering and product teams, you will help build our brilliant energy platform. Your work will directly impact our ability to deliver tailored solutions to clients, release new functionality, optimize energy consumption patterns, and contribute to a more sustainable energy system. We're seeking passionate individuals who want to help us move closer to a net-zero world.

Requirements

What will you do?

• Collect, sanitize, and store large-scale energy consumption data from diverse sources to ensure its quality and relevance for our models, using data pipelines and ELTs.
• Design and implement innovative features capturing complex relationships between energy consumption, external factors (weather, occupancy, etc.), and grid conditions, improving the accuracy of predictive models.
• Develop and train supervised and unsupervised prediction models for understanding energy consumption patterns, participating in demand response opportunities, and forecasting energy market trends.
• Continuously refine and optimize existing models for improved accuracy, interpretability, and computational efficiency.
• Implement mechanisms for real-time anomaly detection and alerting to proactively address unusual energy consumption patterns or system malfunctions.
• Collaborate with domain experts and engineers to integrate machine learning models and insights into actionable solutions for energy management.
• Implement rigorous validation and testing protocols to ensure the reliability and robustness of our models in real-world scenarios.
• Stay up-to-date with the latest advancements in machine learning, energy management, and demand response technologies to enhance the product's capabilities and educate stakeholders.

Required experience:

• Master's or PhD in Math, Statistics, or relevant field with a strong focus on machine learning, statistical analysis, and data manipulation.
• Proven experience in developing, maintaining, and deploying predictive and forecasting machine learning models.
• Strong background in data clustering (correlation and hierarchical algorithms).
• Expert in SQL and Python, DBT, and standard data science libraries and frameworks such as pandas, numpy, scikit-learn, TensorFlow/PyTorch, PySpark, etc.
• Experience with Infrastructure-as-Code, Continuous Integration & Deployment patterns.
• Experience with PostgreSQL, Google Cloud Platform, and BigQuery.
• Excellent problem-solving skills and the ability to think creatively to develop innovative solutions.
• Ability to self-start and work independently in a fast-paced environment, as well as navigate ambiguity and bring structure to problems.
• Ability to manage and prioritize multiple projects and change direction quickly.
• Ability to gather strategic insights beyond the paradigm of statistical significance testing.

Desirable experience:

• Familiarity with energy data, smart grids, demand response, or related fields is a plus.
• Experience with Airflow and/or Airbyte.
• 5+ years of experience as a data scientist, leading a small team.
• Expertise in Python (including asyncio) as a software engineer.
• Previous experience in early-stage startups.
• Experience with GCP, Kubernetes, and PubSub.

Benefits

• Competitive salary (£100,000 - £120,000) plus equity.
• 25 days annual leave + bank holidays.
• Private healthcare.
• Standard pension contributions.
• Annual learning & development budget.