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Resumes, LinkedIn, portfolios, salary negotiation, career switches and freelancing — the non-technical skills that get you hired.
Career Guidance articles
How to Prepare for an Interview in One Week
With one week, how you study matters more than how long. Learning research rates practice testing and spaced practice as the most effective techniques, while rereading leaves people confident but forgetful. This day-by-day plan for data and tech interviews is built on those findings.
Imposter Syndrome in Tech: What the Evidence Says and What Helps
Imposter feelings are common among high achievers of every gender and career stage, according to a review of 62 studies, but no treatment had been formally tested. Here is what the evidence does say, why your own sense of performance is a poor guide, and practical habits that tech and data professionals can use.
Asking for a Raise: Timing, Script and Evidence
A raise is usually decided weeks before the conversation you have about it, when budgets are set for the review cycle. Wage data for people who stay in their jobs shows what a typical increase looks like, and why a well-timed, evidence-based request is worth making. This guide covers timing, evidence and a script.
Building a Personal Brand on LinkedIn
A personal brand is what people would say you are good at when you are not in the room. Survey data shows most tech professionals rarely contribute in public, and those early in their careers contribute least, so a small, consistent habit stands out. This guide shows how to choose a theme and build it.
Cracking the Behavioral Interview: STAR Method
Most candidates know what STAR stands for; fewer have stories ready to use it. Employers such as Amazon and Microsoft recommend STAR for behavioural answers, and Microsoft adds a final step, reflection. This guide shows how to build a bank of eight stories that cover most behavioural questions, and how to adapt them.
Common Resume Mistakes That Get You Rejected
Most rejected data resumes do not fail on qualifications; they fail on presentation. Duty lists, long skill dumps and objective statements hide what the candidate can do. A small Python checker run on a before-and-after example shows the mistakes clearly, and how each fix changes what a reader sees.