Senior Data Scientist (Energy Efficiency)

Job Description: Senior Data Scientist (Energy Efficiency)

Company: Carnot Innovations

Role: Senior Data Scientist

Location: Hong Kong

Job Summary: Carnot is seeking a highly motivated and analytical individual with a strong foundation in Data Science to lead innovative projects. Reporting to the Chief Technology Officer/Co-founder, the ideal candidate will combine technical expertise in data analysis with robust project coordination skills to deliver effective solutions. Knowledge or interest in HVAC systems and energy efficiency is highly preferred.

Key Responsibilities:

Project Delivery & Coordination:

• Technical support on AI optimisation deployment projects from kickoff to handover, following agreed scope, timeline, and budget.
• Coordinate with client representatives, BMS vendors, IT teams, and maintenance contractors to prepare system architecture, point lists, and integration requirements.
• Track project progress, risks, and issues; propose and implement corrective actions to keep projects on schedule.

Client Reporting & Stakeholder Communication:

• Prepare technical reports and presentations showing project status, issues, and performance results (e.g. energy savings, comfort metrics, fault reduction).
• Present AI optimisation outcomes to clients, explaining changes in control strategies and system behaviour in clear, non-jargon terms.
• Collect client feedback on performance, usability, and operational constraints and incorporate it into subsequent iterations.

Problem Solving & Continuous Improvement:

• Investigate anomalies raised by the AI platform (e.g. unexpected control behaviour, inconsistent data, unstable setpoints) and coordinate with project delivery teams to identify root causes.
• Propose practical solutions that balance energy efficiency, system reliability, indoor comfort, and client risk appetite.
• Work with internal data science and product teams to refine analytics, rules, and dashboards based on real-world project experience.

Research & Development:

• Model Innovation & Engineering: Further develop end-to-end machine learning models for high-resolution predictive analytics, load forecasting, and demand-side energy optimization using regression, deep learning, and advanced time-series methods.
• Algorithmic Optimization: Enhance model accuracy and operational efficiency through rigorous feature engineering, model architecture selection, and hyperparameter tuning.
• Agentic AI & LLM Integration: Build advanced retrieval and agentic AI systems utilizing LLMs models to automate complex operational checks, faults detection, and technical report generation.
• Robust Data Architecture: Architect and optimize automated ETL pipelines and data-integrity frameworks to seamlessly process and clean millions of multi-source historical records.
• Technical Mentorship: Drive analytical excellence across the team by reviewing algorithmic outputs, establishing R&D quality standards, and mentoring junior data scientists.

Required Skills and Qualifications:

• Education: Master’s degree or PhD in Data Science, Artificial Intelligence, Computer Science, or a related highly quantitative field.

• Proven track record of developing and deploying production-grade ML pipelines in Python (PyTorch, Scikit-learn, Pandas).

• Deep expertise in relational databases, SQL-based ETL optimization, and automated data quality audits.

• Soft Skills: Strong leadership, problem-solving, and attention to detail, with a demonstrated ability to remain resilient in fast-paced environments.

• Languages: Fluent in English and Cantonese; intermediate Mandarin is an advantage.