SUBMISSION DEADLINE: November 10, 2017
FINAL AWARDING: November 25, 2017
Test your skills in data analytics, visualization and machine learning, and outperform others on your way to victory. The grand winner can win between PHP50,000 to PHP90,000 in cash!
How might you improve the acceptance rate of jobseekers for their preferred roles?
Finding a job that matches an applicant’s skills, experience and values can be tough. Preferred employers are flooded with applications while candidates wait for a long time to hear back for a role that fits their profile.
Kalibrr, a Talent Solutions company, has more than 2 million rows of data from over 400,000 job applicants and over 5,000 employers. Can you make sense of all this data and propose a data-driven solution to optimize the job-to-applicant matching rate, helping job seekers and employers connect successfully?
The data set for this competition is a set of files describing job applicant characteristics and job post information. It is anonymized and contains a sample of over 400,000 candidate profiles that have applied through Kalibrr. For each profile, we provide their work history information, approximated location, skills and preferences. The goal of the competition is to improve the likelihood of a jobseeker’s success in getting hired using predictive and prescriptive analytics.
WHO SHOULD JOIN?
You! Come along if you’re a motivated, sharp, data scientist who gets excited about problem-solving, and believes that data can be a tool for positive change and transform the future of recruitment. No experience is necessary, and you may register as an individual or as a team with a maximum of two members. Professionals and students are welcome to join.
What’s at stake: Up to PHP90,000 cash prize plus a free enrollment to an analytics training course!
Evaluation of the submitted entries will be based on the following pre-defined criteria:
E-mail your entries to Big.Data.Challenge@Accenture.com by November 10, 2017. Entries must be in the form of a power point file that contains the following:
Documentation of the entries:
Introduction: Definition of Terms and Variables, Assumptions, Context of the Problem
Methodology: Approach and technique used in building the proposed model/s
Results: Accuracy of the proposed model, Insights and Recommendations from the proposed model/s
Appendix: Share the source codes/syntax/streams used in the analysis
Visualization representing insights from the dataset (screenshot, file, or link to the visualization)
Predictions for the holdout dataset
Optional 5-minute video presentation. Upload your video on youtube.com (you may set to private) and e-mail us the link.
From November 13 to 17, 2017, the Accenture Data Challenge Core Committee will screen and evaluate all entries and identify the top 20 entries (10 from students, 10 from professionals). The top 20 individuals or teams will be notified via e-email and will be announced on social media starting November 15, 2017.
The top 20 contestants or teams will present and defend their solutions to a panel of judges, after which the winners will be announced. All other contestants who have not made it to the top list will receive an invitation to join the culminating event.