
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ML_FAC
May 21, 2026 – Present
Repository for the machine learning version of the field aligned current model for the AIMFAHR project
View Projectml_rsd
February 18, 2025 – February 18, 2025
Repository containing the work done for publication "Using Machine Learning Explainability Techniques to Examine Drivers of Ground Magnetic Field Localization" by Coughlan et al.
View Projectmutual_information
July 15, 2024 – July 16, 2024
Repository for examining the mutual information between different solar wind and magnetospheric drivers of dB/dt and RSD
View Projectincluding_ion_temp_maps
May 3, 2024 – January 7, 2025
including_ion_temp_maps — GitHub repository
View Projectrsd_sea
January 12, 2024 – November 21, 2024
Repository for superposed epoch analysis of RSD events
View Projectnasa-space-apps-2023-magnetocats
October 6, 2023 – October 10, 2023
2023 NASA Space Apps Challenge for "Develop the Oracle of DSCOVR" - Team Magnetocats
View Projectinterpolation_methods
May 23, 2023 – May 26, 2023
Examining different interpolation methods for replacing missing data. Looking for improvements upon linear interpolation.
View Projectdbdt-difference-analysis
May 9, 2023 – May 18, 2023
Examining the differences in dB/dt measured at magnetometers. Performing statistical analysis to establish baseline difference from which we can define a standard deviation about that baseline to study extreme events.
View Projectmulti-station-dbdt-risk-assessment
September 14, 2022 – July 13, 2023
Performing dbdt risk assessment at multiple magnetometer stations. Determine the probability that the dbdt will exceed the 99th percentile threshold 30-60 minutes into the future.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in scientific research, specifically space weather and geophysics, utilizing Python and Jupyter Notebook. While this demonstrates deep expertise in a niche area, the lack of diversity in project domains (e.g., business analytics, finance, healthcare) and technologies (e.g., SQL, cloud platforms, big data tools) suggests a potentially narrow scope of experience for a general 'Data Scientist' role. This might indicate a need for adaptation to broader industry applications and tools, impacting cultural fit for roles requiring diverse domain knowledge or a wider tech stack.
Soft Skills & Operational Fit
The candidate's project descriptions suggest a strong analytical mindset and a focus on problem-solving. The nature of the projects (research-oriented, scientific data) implies a capacity for independent work and detailed investigation. However, without specific assessment data on communication, teamwork, or stress handling, it is difficult to fully assess soft skills and operational fit.