Very proud of the latest cohort of Data Science thesis interns at Randstad Groep Nederland. In absence of a “real” defense at the University of Amsterdam, we organized our own afternoon packed with defenses (and subsequent drinks) in our Randstad HQ in Diemen. At the end of the afternoon we were able to congratulate Roan, Anna, and Adam on a job (almost) well done!
Roan Schellingerhout presented his work on “Explainable career Path Predictions.” Roan implemented explainable deep neural nets for predicting and explaining a job seekers’ next opportunity, given their previous. He evaluated the models intrinsically, in addition to testing them (+ their explanations) with actual recruiters, and found both that models are accurate and recruiters like and understand them.
Anna Lőrincz worked on data-to-text generation, and fine-tuned a multilingual transformer model for generating benefits (salary, contract, working hours, locations) in job descriptions in both Dutch and English, given structured information (numeric, categorical, and binary variables). She found that transformers can successfully generate fluent and correct text given structured inputs, confirmed that inputs or prompts have a high impact on performance, and found that her approach beats template-based methods in textual diversity. She also found a few very funny hallucinated work locations (“pal achter centraal station in Zwaaijdijk”, was one of our favorites), and found that transformer models tend to sometimes correct output (adjusting a 3k/hour salary into a 3k monthly salary).
Finally, Adam Mehdi Arafan presented his “Double Fair-Gated Bias Mitigation Pipeline” for our Talent Recommender system, where he studied bias in multiple parts of our recsys pipeline, from re-balancing training data (to simulate both balaned and highly imbalanced scenarios), to generating additional balanced synthetic data, and re-ranking outputs. Turns out applying synthetic data does not only help in creating more fair rankers, but can also have benefits in terms of model accuracy!
All three students did great jobs, stay tuned for their thesises (and, who knows, publications? 😏)
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