Senior Data Scientist

About this role

Data owns the pipelines, the warehouse and the definitions the business argues about — funnel conversion, time to hire, source quality.

Work on candidate–role matching and resume understanding. Models here affect who gets seen, so evaluating for bias is part of the work rather than a review step at the end.

The hard part is not the pipeline; it is that two teams asking the same question must get the same answer. Most of the work is in the semantic layer and in being willing to say a number is not trustworthy yet.

Primary responsibilities

• Work on the questions where the answer changes a decision: what predicts a good hire, where the funnel really loses people, what a change was actually worth
• Design and analyse experiments properly — power, the metric chosen in advance, and the discipline not to go looking afterwards
• Build models that go into production, and own their behaviour once they are there
• Be the person who says the data does not support the conclusion, including when it is inconvenient
• Communicate uncertainty in a way a decision-maker can actually use

Skills required

Day to day this role works with Python, Machine Learning, Statistics and NLP.

• Five or more years applying ML to a product, including the parts that did not work
• Able to explain a model’s failure modes to someone who will act on the answer
• Five or more years in data science with production impact
• Strong statistics — experimental design, power, and the discipline not to go looking after the fact
• Python and SQL to a production standard
• Machine learning applied to real problems, with honest evaluation