Staff Validation Scientist - Machine Learning and Catastrophe Models

Menlo Park /
Data Science /
Full Time
One Concern is a Menlo Park-based benevolent artificial intelligence company with a mission to increase the global community's resilience to natural hazards. Founded at Stanford University, One Concern enables cities, corporations, and citizens to embrace a disaster-free future through AI-enabled technology, policy, and finance. By combining data science and natural phenomena science we are pursuing a vision for planetary-scale resilience, where everyone lives in a safe, equitable, and sustainable world.

One Concern is growing rapidly and we are looking for a passionate and motivated Staff Validation Scientist in Machine Learning and Catastrophe Models to join our team. In your role, you will lead the overall Model Risk Management Framework, and be responsible for execution of validation activities for disaster models, model performance evaluations, and working with product teams to ensure that models and metrics meet customer objectives.

Responsibilities

    • Evaluate machine learning and physics-based catastrophe models for multiple types of disasters and their impacts to people and property, while collaborating closely with the model development teams
    • Define validation metrics and implement measurements and validation processes to effectively challenge the model development process, conceptual soundness, model performance, implementation, and appropriateness of model use
    • Manage the overall Model Risk Management Framework, revise as necessary based on new challenges and business needs
    • Clearly communicate and document findings to internal and external stakeholders in a collaborative manner
    • Ensure compliance with widely accepted standards
    • Manage external independent validation process and track incorporation of their feedback by model development teams
    • Must be available to work on-site when One Concern's office re-opens, currently projected for 2021

Requirements

    • Ph.D. or Master’s degree in civil engineering, statistics or related field with emphasis on disaster risk 
    • Strong background in probability and statistics, and quantitative risk assessment
    • Experience in developing and validating machine-learning models
    • Knowledge of and experience in statistical tools like R or relevant libraries in Python like scikit, sklearn
    • Ability to assess model conceptual design, back-testing of model results, theoretical underpinnings and assumptions, and compliance of model results with intended application by model users
    • 2-3 years of related experience in hands-on model development or validation for disaster risk
    • Strong attention to detail
    • Communication and leadership experience, with experience initiating and driving projects
    • Mission driven

Nice to Have

    • Experience in leading projects
    • Experience in creating and implementing machine learning validation processes
    • Experience in one or more of the following - flood inundation modeling, seismic hazard analysis,  vulnerability modeling

Perks and Benefits

    • Market-competitive salary plus equity
    • Comprehensive medical, dental, and vision insurance
    • Daily catered lunches, and a fully-stocked kitchen
    • Generous PTO policy
    • Team off-sites
    • Flexible working hours