Sr. Manager, Agronomic Data Science

• Feb 2023 - Present

Staff Data Scientist

• Jun 2021 - Dec 2022

Lead remote sensing data scientist for Carbon Ecosystems Services modeling. I developed and standardized our workflow for developing large-scale predictive models ingesting satellite imagery across millions of acres, and concurrently trained models to determine planting and harvest date, cover cropping, and tillage practices. I validated these models against external stakeholder data and worked to productionalize their predictions to allow farmers to get paid for taking up greener… Show more Lead remote sensing data scientist for Carbon Ecosystems Services modeling. I developed and standardized our workflow for developing large-scale predictive models ingesting satellite imagery across millions of acres, and concurrently trained models to determine planting and harvest date, cover cropping, and tillage practices. I validated these models against external stakeholder data and worked to productionalize their predictions to allow farmers to get paid for taking up greener practices. I passed Corteva's Agronomy Essentials, a 16-week course in large-scale agriculture in the United States; I was the first on the Data Science team to bring this knowledge to our model development. As the most senior scientist on the team, I contributed significantly to our learning culture, giving a number of talks and demos on varied mathematical, statistical, and scientific topics. I also promoted a culture of software engineering best practices, including around testing, documentation, type hints, and CI/CD. Show less Lead remote sensing data scientist for Carbon Ecosystems Services modeling. I developed and standardized our workflow for developing large-scale predictive models ingesting satellite imagery across millions of acres, and concurrently trained models to determine planting and harvest date, cover cropping, and tillage practices. I validated these models against external stakeholder data and worked to productionalize their predictions to allow farmers to get paid for taking up greener… Show more Lead remote sensing data scientist for Carbon Ecosystems Services modeling. I developed and standardized our workflow for developing large-scale predictive models ingesting satellite imagery across millions of acres, and concurrently trained models to determine planting and harvest date, cover cropping, and tillage practices. I validated these models against external stakeholder data and worked to productionalize their predictions to allow farmers to get paid for taking up greener practices. I passed Corteva's Agronomy Essentials, a 16-week course in large-scale agriculture in the United States; I was the first on the Data Science team to bring this knowledge to our model development. As the most senior scientist on the team, I contributed significantly to our learning culture, giving a number of talks and demos on varied mathematical, statistical, and scientific topics. I also promoted a culture of software engineering best practices, including around testing, documentation, type hints, and CI/CD. Show less

Principal Data Scientist

• Apr 2019 - Jun 2021

Head of the CBRE Build Data Science Team. Managed direct reports, grew the data science team from one to five people, and developed collaborations across multiple projects, offices, and departments. Won the Ambassador Award in 2020, delivered annually to twelve employees across the USA and Canada (over 800 nominees from 38,000+ employees). Project lead and core modeler exploring the impact of COVID-19 on corporate revenue. Combined epidemiology with custom economic damage models and… Show more Head of the CBRE Build Data Science Team. Managed direct reports, grew the data science team from one to five people, and developed collaborations across multiple projects, offices, and departments. Won the Ambassador Award in 2020, delivered annually to twelve employees across the USA and Canada (over 800 nominees from 38,000+ employees). Project lead and core modeler exploring the impact of COVID-19 on corporate revenue. Combined epidemiology with custom economic damage models and time-series forecasting methods to construct scenarios used by C-Suite to inform strategic decisions in response to changes in market dynamics. The work was recognized by the CBRE Technical Excellence Award in September 2020. Team lead on a large lease abstraction initiative. Developed ML pipelines to extract over one hundred attributes from unstructured legal documents. Guided a team new to natural language processing in cutting-edge NLP methods and transfer learning. Productionalized the models as a pipeline of APIs in a kubernetes cluster. Subject matter expert, digital user behavioral analytics. Built Python packages for handling and analyzing user event data; developed best practices around application tracking; constructed automated user archetype analytics to empower product managers with insightful information. Founded the Data Science Round Table, a grassroots meeting of data practitioners at CBRE for peer review, support, and collaboration. Mentored data scientists locally and offshore in machine learning, statistical methodology, and software engineering.

Senior Data Scientist

• Apr 2018 - Apr 2019

Data Scientist

• Mar 2016 - Apr 2018

Course Creator - Python for Scientific Computing

• Dec 2013 - Mar 2016

This course introduces programmers to Python's scientific computing tools. After a fast-paced refresher on syntax, we cover Python's primary scientific stack - numpy, scipy, matplotlib, and pandas. The course consists of an in-depth introduction to these packages, interspersed with hands-on exercises to reinforce what is being presented. By the end of the course, we will have performed some exploratory statistical analysis on a real dataset, using these tools to gain information on the… Show more This course introduces programmers to Python's scientific computing tools. After a fast-paced refresher on syntax, we cover Python's primary scientific stack - numpy, scipy, matplotlib, and pandas. The course consists of an in-depth introduction to these packages, interspersed with hands-on exercises to reinforce what is being presented. By the end of the course, we will have performed some exploratory statistical analysis on a real dataset, using these tools to gain information on the underlying patterns present in the data.

Postdoctoral Researcher

• Mar 2013 - Mar 2016

I am a postdoctoral researcher with the Grenfell Group at Princeton University. I work primarily on the dynamics of infectious diseases, studying the epidemiology of measles in small populations. I also develop algorithms for robust extraction of information from images, to quantify structural measures of degeneration in histological samples.

PhD Student

• Sep 2009 - Mar 2013

My research was aimed at understanding the role of dendritic morphologies and synaptic properties in the dynamics of neuronal networks. I was affiliated with the Institute of Mathematics, the Department of Computer Science, and the School of Life Sciences, and a member of the Computational Biology and Bioimaging Group.

Module Creator - Introduction to Scientific Computing

• Oct 2010 - Jun 2012

The Introduction to Scientific Computing minimodule aims to provide a very basic level of introduction in scientific computing. We will use C programming and Matlab, applied to various mathematical topics such as cellular automata, data analysis and random walks.

Junior Scientist

• Jun 2004 - Aug 2004