Education

Stanford University – M.S. in Environmental Engineering | March 2021

Stanford Graduate School of Business – Stanford Ignite | March 2020

Marquette University – B.S. in Mechanical Engineering | December 2015

University College Dublin – Semester Exchange Program | Spring 2013

Experience

Product Manager | Flodesk | San Francisco, CA December 2023 - Present

Flodesk makes simple, intuitive software tools to help you grow your business.

Head of Product | Terrafuse AI | San Francisco, CA June 2021 - August 2023

Terrafuse AI is developing the most advanced climate and weather risk prediction solution on the market by leveraging deep expertise and pioneering research in physics-enabled machine learning.

  • Promoted to Head of Product by delivering two climate model products with over $1.5M in revenue in the first 18 months of the job.

  • Designed Insurance Go-to-Market strategy for B2b Wildfire API, launching a free trial offering with 40+ enterprise accounts which led to the company's first recurring revenue.

  • Created and presented all customer geospatial and statistical data for business development, leading to 2x the number of paid pilot projects.

  • Instituted customer discovery process to align machine learning metrics with customer needs, resulting in a model with a 33% predictive performance increase for burned locations.

  • Revamped product development process by transitioning to agile development framework, streamlining user story development and accelerating development cycle time by ~75%.

Project Manager | Stanford Woods Institute for the Environment | Stanford, CA March 2020 – June 2021

The Stanford Woods Institute for the Environment is working toward a future in which societies meet people’s needs for water, food, health and other vital services while sustaining the planet. Part of the Stanford Doerr School of Sustainability, Woods is the university's hub for interdisciplinary research about the environment.

  • Project Manager for Dept. of Energy FERC initiative investigating the value of aggregating water-related data for improved basin management, culminating in a workshop with 80+ stakeholders from government, nonprofit, and research institutions.

  • Coordinated interviews from multiple agencies, provided critical feedback to stakeholders to use data to improve the quantification of trade-off decision making.

  • Successfully managed all aspects of the project from initiation to completion of deliverables within time and budget constraints.

Product Management Intern | Imagine H2O | San Francisco, CA June 2020 – August 2020

Imagine H2O is a nonprofit organization that empowers people to develop and deploy innovation to solve water challenges globally.

  • Led product development, testing, and implementation of Imagine H2O's digital platform connecting over 750+ startups, customers, and investors to cut internal time spent facilitating introductions in half.

  • Evaluated 50 water technology startups for the Urban Water Challenge looking at their relevance to the accelerator and their potential market impact.

Technology Consultant | Accenture Federal Services | Washington, DC February 2016 – March 2019

Accenture is a global professional services company with leading capabilities in digital, cloud, and security.

  • Received two promotions in three years for successfully delivering two multi-million dollar enterprise Salesforce products as a Product Owner.

  • Delivered a medical grants management system which has funded $2.8 billion in awards and doubled the organizations grant capacity, ultimately leading to faster medical breakthroughs such as cancer screening methodologies that are five times more effective.

  • Managed Scrum development teams of 8+ members to create a permitting system which delivers 40k+ permits annually for the U.S. Department of Agriculture, including the first ever automatic permit issuance to reduce time spent by staff supporting customers.

  • Designed product roadmaps, technical requirements, and user stories through 1000+ hours of client meetings and workshops.

Research

Graduate Researcher | Natural Capital Project | Stanford, CA January 2020 – March 2020

  • Utilized GIS for the creation of data to assess land use changes, development, and average water availability for optimal irrigation in the US. Results indicated a potential future irrigation application rate increase of 2.6x to 1601 (mm/year).

  • Designed, and developed reusable GIS components in Python/ QGIS for water consumption and irrigated areas, allowing data to be processed quickly, accurately, and efficiently.

  • Created data visualizations from geospatial data and collaborated in writing and testing code for spatial interpolation methods.

Volunteer

Content Contributor | Climate Mind | Stanford, CA January 2021 - April 2021

GIS Analyst | Reflective Earth | Stanford, CA January 2021 - March 2021

Projects

Forecasting Air Pollution | [Project Github Web App]

  • Deep learning project to forecast PM 2.5 concentrations.

Soil Moisture Analysis | [Github]

  • Investigated the correlation between soil moisture and land cover type using remote sensing data in python.

Quantifying Wind Energy | [Github Medium]

  • Calculated potential energy production from wind in northern california using NOAA climate data.

Soccer Match Prediction | [Github]

  • Composed a Premier League match result prediction program in Matlab.

Wildfire Evacuation GIS Tool | [Github Page]

  • Developed prototype for a geospatial evacuation route mapping tool.

Technical Skills

Product Management, Quantitative Analysis, Data Visualization, Project Management, Stakeholder Engagement and Communication, Customer Discovery, Business Development, Trade-off Decision Making, Academic Research

Development Methodologies | Agile, Waterfall

Programming | Python, SQL, Matlab

Data Science Packages | Pandas, Numpy, Keras, SciPy, Scikit-learn, Seaborn

Web Development | Streamlit, Django, HTML, CSS

Database | PostgreSQL

Platform | Google Cloud Platform, Salesforce, Heroku

Software | JIRA, Asana, Tableau, Minitab

GIS | ESRI ArcGIS, QGIS, Google Earth Engine, Rasterio

Design | Figma, Canva, Affinity Designer, Affinity Photo

Certifications | Awards

  • Accenture US Corporate Citizenship Volunteer Award Winner

  • Salesforce Admin 201

  • Dataquest.io - SQL Skills Path

  • Deeplearning.ai - Deep Learning

  • BerkeleyX - Data8.1x: Foundations of Data Science: Computational Thinking with Python

Relevant Coursework

CS106A Programming Methodology | Introduction to the engineering of computer applications emphasizing modern software engineering principles: program design, decomposition, encapsulation, abstraction, and testing in the Python programming language.

CS230 Deep Learning | Learned the foundations of Deep Learning, how to build neural networks, and how to lead successful machine learning projects. Topics covered include: Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more.

CEE 260D Remote Sensing of Hydrology | Topics covered include the hydrologic cycle, relevant sensor types and the electromagnetic spectrum, active/passive microwave remote sensing (snow, soil moisture, canopy water content, rainfall), thermal sensing of evapotranspiration, gravity and hyperspectral methods, as well as an introduction to data assimilation and calibration/validation approaches for hydrologic variables.

ESS 239 Data Science for Geoscience | This course provided an overview of the most relevant areas of data science (applied statistics, machine learning & computer vision) to address geoscience challenges, questions and problems. Using actual geoscientific research questions as background, principles and methods of data scientific analysis, modeling, and prediction were covered. Data science areas covered include: extreme value statistics, multi-variate analysis, factor analysis, compositional data analysis, spatial information aggregation models, spatial estimation, geostatistical simulation, treating data of different scales of observation, spatio-temporal modeling (geostatistics). Application areas covered include: process geology, hazards, natural resources.

CEE 266F Stochastic Hydrology | This course introduced the statistical methods used in hydrology for data analysis, risk and uncertainty analysis, and simulation. Topics include: flood and drought frequency, time series analysis, rainfall-runoff modeling, and lake water quality. Methods include: applied probability theory, extreme value theory, parameter estimation, regression, time series analysis, transfer functions, Bayesian methods.

CEE 265A Resilience, Sustainability and Water Resource Development | Sustainability and resilience concepts are illustrated using cases studies involving water development agencies in the US and other counties. These studies illustrate the role of political, social, economic, and environmental factors in decision making. Topics include multipurpose dams, structural and non-structural flood control measures, and drought management strategies. The course also examines the work of international aid organizations and NGOs in promoting sustainability and resilience in water resources development.

CEE 266A Watersheds and Wetlands | Introduction to the occurrence and movement of water in the natural environment and its role in creating and maintaining terrestrial, wetland, and aquatic habitat. Hydrologic processes, including precipitation, evaporation, transpiration, snowmelt, infiltration, subsurface flow, runoff, and streamflow. Rivers and lakes, springs and swamps. Emphasis is on observation and measurement, data analysis, modeling, and prediction.

CEE 278A Air Pollution Fundamentals | The sources and health effects of gaseous and particulate air pollutants. The influence of meteorology on pollution: temperature profiles, stability classes, inversion layers, turbulence. Atmospheric diffusion equations, downwind dispersion of emissions from point and line sources. Removal of air pollutants via settling, diffusion, coagulation, precipitation, Mechanisms for ozone formation, in the troposphere versus in the stratosphere. Effects of airborne particle size and composition on light scattering/absorption, and on visual range.