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The likely match for “A Data Scientist Shares His Passions” is INRIX’s March 8, 2022 employee spotlight on Joshua Kidd. In it, Kidd connects his work in data science—finding useful patterns in data and building predictive models—with hobbies that include running Dungeons & Dragons games, playing board games and hiking. The profile places him at INRIX’s Altrincham, Manchester office; it does not establish whether he still works there today.
From mathematics to applied data science
Kidd studied Mathematics and Statistics at Lancaster University. He says a medical-statistics module particularly influenced him because it showed how statistical methods could address real-world problems. Trial design, stratification and evaluating historical data were among the ideas he found relevant to his later work. He also stresses that statistics alone are not enough: understanding the subject area helps make analysis useful.
In the 2022 profile, Kidd describes INRIX as his first job after university. He says he joined as a data analyst and progressed to data scientist. His account is a snapshot of that career at the time, not confirmation of his current role.
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What data scientists do, in Kidd’s account
“Ultimately, the aim of a data scientist is to gain actionable insights from data, although that definition is probably too concise to be helpful,” Kidd says in the profile. He cautions that the job varies considerably by employer. Analysis can help interpret a dataset; data science may also apply statistical techniques such as machine learning to build models that predict future events.
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At INRIX, Kidd says, his team explored whether new features or model architectures could improve existing algorithms or support new products. One example he describes is predicting travel mode from GPS points. INRIX uses GPS location information to predict road speeds, but data gathered through mobile-navigation apps may come from someone walking, cycling, driving or riding a train. A model that estimates a trip’s mode can help distinguish those cases.
Kidd also describes using active learning to choose which unlabeled GPS traces people should label for the next model iteration. The approach prioritizes examples for which the current model is least confident. That is his description of the project; the profile does not report measured performance or independently assess the method.
His advice for people starting out
Kidd’s advice centers on applying skills and explaining decisions, not just producing a working model. For a project, he recommends being able to describe its goal, why you chose a particular model and features, and how you decided whether it succeeded.
- Build practical experience. Kidd points to Kaggle as a source of datasets and problems to practise on. He cautions learners to understand and justify their own choices rather than copy someone else’s code.
- Learn tools for working with data. He names Python and its libraries NumPy, SciPy and pandas, as well as JupyterLab. He also recommends SQL because data is often stored in databases.
- Meet other learners and practitioners. He suggests local meetups and hackathons as opportunities to learn and connect with peers.
- Communicate clearly. Findings need to make sense to nontechnical colleagues as well as technical teams. Kidd’s practical reminder is: “A final pet peeve of mine, always label your graphs!”
The games and places he enjoys
Outside work, Kidd says he runs Dungeons & Dragons sessions for friends and enjoys the storytelling. He also names two board games he likes, each built around a different kind of play.
- Food Chain Magnate is a competitive game in which players build rival fast-food companies.
- The Quiet Year is a collaborative storytelling game about a community rebuilding after the collapse of civilization; players develop the story by adding to a map.
Kidd also says he loves hiking and names the Swiss Alps around Kandersteg as a favorite place. These are personal interests described in the 2022 profile, not evidence of current travel plans.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.About the profile
This article is based on INRIX’s Employee Spotlight: Joshua Kidd, Data Scientist, published March 8, 2022. It is a primary source for what Kidd and INRIX said at the time. It does not establish his present employment status or independently verify the results of the project he describes.
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