Data Scientist – AI Benchmark Architect

Data Scientist – AI Benchmark Architect

Requirements

• MS/PhD in Data Science, Computer Science, Mechanical/Electrical Engineering, Civil Engineering, or equivalent experience.
• Strong statistical analysis skills and experience with machine learning techniques
• Proficiency in programming languages (Python, C++, Swift, Rust, etc)
• Exceptional Communication Skills: Demonstrates the ability to effectively articulate complex technical concepts related to deploying autonomous systems and advanced programming in Swift. Excels at translating technical features into compelling narratives that resonate with both technical and non-technical audiences.
• Organized and Strategic: Skilled in planning and executing the deployment of autonomous systems with precision, ensuring all aspects—from system integration to scalability—are managed with a high level of attention to detail.
• Collaborative Mindset: Thrives in team environments, working closely across disciplines to align strategies for system deployment, programming, and sustainable design with overarching project and organizational goals.
• Adaptability: Comfortable in a fast-paced startup environment, eager to learn, iterate, and innovate.
• Problem solving: You own this role. When issues arise, be the empowered force that solves them, rolling-up.

Responsibilities

• Ability to define and interpret key performance indicators (KPIs) for autonomous systems, such as accuracy, latency, robustness, and efficiency. Expertise in designing meaningful benchmarks that evaluate real-world performance.
• Acquire and manage a variety of data including sensors and control data from PassiveLogic’s deployed Hive Controller systems, and virtual data from the simulation environment.
• Conduct an in-depth analysis of the collected data, identifying patterns, insights, and anomalies that can influence the system’s performance. Collaborate with the Formal Methods team to provide refinement ideas to automate the physical and statistical-based testing of our systems and algorithms in simulated and deployed buildings.
• Create evaluation metrics that measure the performance and fairness of AI models across diverse tasks. They ensure that benchmarks are comprehensive, reproducible, and aligned with real-world applications while actively collaborating with the open-source community to promote transparency, inclusivity, and innovation.
• Communicate complex data findings to technical and non-technical stakeholders, including creating visualizations, reports, and presentations.

Preferred Qualifications

• Understanding of the built environment and cyber-physical systems: Demonstrate a strong knowledge of how physical infrastructure integrates with digital technologies, enabling the creation of intelligent and adaptive systems.
• Experience with validation frameworks for autonomous systems: Proven ability to design and implement robust validation frameworks to ensure the reliability and performance of autonomous systems across diverse conditions.
• Proficiency in reasoning and inferencing: Skilled in applying advanced reasoning and inferencing techniques to enhance decision-making processes and optimize system intelligence.
• Experience with relational databases: Demonstrated experience in managing and optimizing relational databases like PostgreSQL and MySQL to efficiently store, retrieve, and analyze complex datasets.
• Familiarity with building energy modeling software: Knowledgeable in tools such as EnergyPlus, Modelica, and IES, leveraging them to simulate and optimize building energy performance and sustainability.
• Experience in deploying autonomous systems: Demonstrated expertise in implementing and integrating autonomous systems, ensuring reliable performance, scalability, and seamless functionality across diverse environments.
• Proficiency with Swift programming language: Skilled in utilizing Swift to design, develop, and optimize software applications, leveraging its advanced features to deliver efficient and scalable solutions.
• Solid understanding of building physics and HVAC systems: Comprehensive knowledge of building physics, including heat transfer and HVAC systems, enabling the creation of energy-efficient and sustainable designs tailored to complex operational requirements.