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Resumes, LinkedIn, portfolios, salary negotiation, career switches and freelancing — the non-technical skills that get you hired.
Career Guidance articles
Resume Building for Data Roles: A Complete Guide
A data resume has to pass software filters and a hurried human reader. US Department of Labor data shows which tools are classed as in demand for analyst, scientist and data warehousing roles, and which verbs describe the work. This guide turns that into a structure, bullet formula and checklist.
LinkedIn Optimization for Tech Job Seekers in 2026
LinkedIn advice usually stops at keywords and a good photo, but the best evidence points at your network. A randomised experiment with over 20 million members showed which connections lead to new jobs. This guide covers that evidence, Open to Work settings including India's, and a profile checklist.
Interview Tips for Freshers: How to Stand Out
Most freshers have similar degrees and similar resumes, so interviews are where they separate. Employer surveys show skills-based hiring is now the norm, and that employers want examples of skills in use, not lists. This guide shows freshers how to turn coursework and projects into evidence and handle each round.
Career Switch to Data Science: A Realistic Roadmap
Most data scientists hold a master's degree or a doctorate, and that shapes any realistic career switch. Data from O*NET and from 574 working data scientists shows the education, experience and tools the job really involves, and why moving through an analyst role first is the most reliable route for career changers.
Salary Negotiation: How to Get Paid What You're Worth
In negotiation experiments, whoever made the first offer usually got the better deal, and first offers strongly predicted the final price. The same research shows how to neutralise an anchor: focus on your own target and alternatives. This guide turns those findings into a practical plan for negotiating a job offer.
Portfolio Building: Projects That Impress Recruiters
Recruiters and hiring managers spend minutes, not hours, on a portfolio, so a project has to show its value fast. This guide gives the rubric a reviewer applies to any tech or data project, a README structure based on GitHub's guidance, the licence checks most portfolios skip, and how to reuse each project.