The Unique Challenges Startups Face Hiring Data Scientists

A Thirst For Technical Talent

The Problem With Outsourcing Tech

  • Vetting talent — Without at least one expert on the in-house team, it becomes difficult for C-suite and project managers to vet talent. Someone must have the technical experience to conduct reliable interviews and ensure a good fit with the overall data strategy.
  • Competing with big names — It’s a vicious cycle. Small companies outsource their tech while big companies scoop up talent. Talent doesn’t want to come into fix or build solutions for a small company; they want to work on cutting edge projects with established names, so they flow there. Rinse and repeat.
  • Global disruptions slow the appetite for risk — Startups are risky. Without guaranteed revenue streams or even a guaranteed job in three to five years, candidates are making “safe” decisions going with large companies unlikely to go bottom-up. With so many jobs already affected, workers could be staying put.

Sourcing Data Talent and Hiring Data Scientists

  • Startups are trying to compete on FAANG terms with salary and equity instead of offering their own unique benefits.
  • Startups cannot properly vet the senior talent they need to build a solution from the ground up. Exams at Upwork are only for the junior level, for example, and startups have no one on the team with the expertise.
  • Startups are waiting for the perfect candidates to come to them instead of aggressively courting talent.
  • Startups are waiting for unicorn talent when the perfect candidate doesn’t actually exist.

What GetAIPlus.com Can Do for Hiring Data Scientists

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