Hiring is one of the toughest data science challenges companies face. I have built 4 data science teams from the ground up and been in almost a hundred interviews. I built the Data Science Hiring pack from lessons learned across eight years in data science and over a decade building and leading technical teams.
The Hiring Guide covers concepts from the first data science hire to building data science teams for businesses in advanced stages of machine learning maturity. I have designed the guide to be something the business comes back to as its hiring needs change and grow. No matter what stage of adoption or maturity the business is in, this guide is meant to insure staffing levels and talent can support the business.
The Hiring Guide includes:
Hiring a Data Science Generalist: The initial two to three hires will be data science generalists. I review the necessary capabilities, assessment methodology, and ways to attract qualified generalists to the business.
Hiring Data Science Teams: The search for unicorns, data scientists with near impossible to find skillsets, is perpetuated by a lack of team building expertise. I cover team structure, individual skills sets, and how each team member contributes to data science projects. At each phase of machine learning maturity, the team structure changes to support the needs of the business. I cover how to successfully staff for the transitions.
Hiring Plan: The hiring plan is designed to help the business understand how many employees the business will need to support their projects, what to budget for recruiting/salary/benefits, and how long the process will take. It’s a plan that can be revisited annually as part of the strategy planning process so hiring stays in line with business needs.
Recruitment Guide: Attracting data science and machine learning talent is unlike any other recruitment challenge. I cover where to go to discover hard to find data science talent and what messages appeal to their unique motivations.