Lead Data Scientist | Data Engineer | Data Governance

I am a self-motivated Data Scientist with over 15 years of experience in data collection, modelling, and analysis for a variety of applications. I leverage Big Data to build actionable products for government and enterprise clients, with a strong emphasis on positive social impact. My multidisciplinary background spans university research, industry, start-ups, and international settings.

DATA ANALYSIS | DATA ENGINEERING | DATA GOVERNANCE | DATA FOR SOCIAL GOOD

• Role: Lead Data Scientist at the Flowminder Foundation working on extracting insights from mobile phone data, survey & census data, and geospatial data.
• Mission: Undertaking high-quality, peer-reviewed humanitarian data science to improve public health and welfare in low- and middle-income countries around the globe.
• Focus: Developing scalable telecoms data pipelines, engaging with Mobile Network Operators as a principal technical liaison, and building Bayesian geostatistical and ML models.
• Active Explorations: Pattern-of-life analysis, anomaly detection, Bayesian optimisation, feature extraction for high-frequency multivariate time-series data, and distributed systems for analytics including MPP and Spark.

Core Proficiencies

• Big Data Analytics, Machine Learning, and Statistics.

Data Processing, Analysis & Modelling

• Python: dask, rasterio, xarray, geopandas, PyTorch, sk-learn.
• R: sf, terra, R-INLA, spdep, spatialreg, tidyverse.
• Core Data Tools: SQL, Airflow.

Geospatial Technologies

• QGIS, Google Earth Engine, STAC, GDAL, PostGIS, MapLibre/Mapbox GL.

Data Visualisation

• R-shiny, matplotlib, seaborn, ggplot2, kepler.gl, grafana, streamlit.
• Designing interactive and effective visualizations tailored for humanitarian responders.

Cloud, MLOps & DevOps

• Platforms: AWS, GCP.
• Infrastructure & CI/CD: Terraform, ansible, packer, vagrant, docker, CircleCI, Github Actions.
• MLOps: DVC, MLflow.

• Education: Engineering Doctorate (EngD) in the prediction and control of sound propagation in turbofan engine bypass ducts from the University of Southampton in collaboration with Rolls-Royce plc. First Class BEng in Acoustical Engineering.
• Past Experience: Postdoctoral Research Fellow developing advanced statistical models for aerospace design with Airbus and Rolls-Royce, and building IoT analytics for UK Olympic athletes. Independent Data Scientist consulting via Brooks Analytics Limited.
• Awards: Co-recipient of the 2023 Better Satellite World Award. Won the 2016 Global Mobile Award for 'Mobile in Emergency or Humanitarian Situations'. Part of the Performance Sport Engineering team awarded the 2011 Queen's Anniversary Prize for Higher and Further Education.

• Steele, J.E., Pezzulo, C., Albert, M., Brooks, C.J. et al. Mobility and phone call behavior explain patterns in poverty at high-resolution across multiple settings. Humanit Soc Sci Commun 8, 288 (2021).
• Wilson R, zu Erbach-Schoenberg E, Albert M, Power D, Tudge S, Gonzalez M, Guthrie S, Chamberlain H, Brooks C, et al. Rapid and Near Real-Time Assessments of Population Displacement Using Mobile Phone Data Following Disasters: The 2015 Nepal Earthquake. PLOS Currents Disasters. 2016 Feb 24. Edition 1.
• Guilherme Augusto Zagatti, Miguel Gonzalez, Paolo Avner, Nancy Lozano-Gracia, Christopher J. Brooks, et al. A trip to work: Estimation of origin and destination of commuting patterns in the main metropolitan regions of Haiti using CDR. Development Engineering, Volume 3, 2018, Pages 133-165.
• Brooks, Christopher James, Forrester, A.I.J., Keane, A.J. and Shahpar, S. Multi-fidelity design optimisation of a transonic compressor rotor. 9th European Conf. Turbomachinery Fluid Dynamics and Thermodynamics, Turkey. 2011.

• Website: brooks-analytics.com
• LinkedIn: in/brooks-analytics
• Research: Google Scholar | ORCID