Football Data Engineer | Open-Source Tech Aficionado. Previously at Norwich City FC, Orlando City SC, Royal Antwerp FC, Nashville SC.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
acciotables
April 18, 2020 – April 18, 2020
API to scrap data from dynamic webpages. (say tables on Sports Reference websites)
View Projectentries-into-final-third
March 28, 2020 – April 1, 2020
Code and Shiny App to Generate "Entries into Final 3rd" Soccer viz. (StatsBomb event data).
View Projectudrmm
February 26, 2020 – May 19, 2020
A Remote Monitoring and Management Tool for Educational Institutes using PowerShell Universal Dashboard.
View ProjectSmartEnergyMonitor
December 1, 2019 – December 1, 2019
An IoT project to monitor electricity usage.
View ProjectDateExtraction
December 1, 2019 – December 3, 2019
An application to extract dates in different formats from an image.
View ProjectKadambaInternship
July 25, 2019 – July 25, 2019
Work Samples from my Summer Internship at Kadamba as Data Analyst (Cricket)
View ProjectstatsguRu
May 12, 2019 – July 1, 2021
R Package for Visualising Cricket Statistics (Data from ESPNCricinfo.)
View ProjectOptical_Player_Tracking_System_For_Soccer
April 22, 2019 – April 22, 2019
A new and non-invasive method of tracking Players in a Soccer Match.
View Projectns2-docker
February 3, 2019 – April 11, 2019
A Docker image to run NS2 and Tracegraph applications
View ProjectFootball-Match-Prediction-Using-R
January 4, 2019 – November 27, 2019
Predicting the result of a Football match using Statistical Modelling in R Programming Language
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards personal interest-driven data science, particularly in sports. This indicates a self-starter who can apply technical skills to specific domains. However, the lack of professional experience or team-based projects makes it difficult to assess collaboration or broader cultural fit within a corporate environment. The diversity of tools (Python, R, C++, PowerShell, Dockerfile) suggests adaptability, but also a potential lack of deep specialization in any single area relevant to a typical Data Scientist role beyond sports analytics.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.