7. Analytics for
Machines or People?
• e.g. Ad targeting,
recommendation
engines
• Need strong
mathematical, statistical
and computational
fluency to build models
that can quickly make
good predictions
• e.g. Analyzing products,
understanding user
growth and retention,
producing reports
• Need to be able to tell
a story from the data,
drawing conclusions
about the “how” and
“why”
8. Hire for talent, train for tech skills
Second
Analytical thinking and good communication
skills are harder to teach than SQL, Python,
R, Java…
9. Third
Broaden your pool of candidates
Diversity
Increases your revenue
Promotes innovation
Provokes more thought, jolts cognitive action
Think outside the box when looking
10. Remember
Define your data needs
Hire for talent, teach tech skills
Look outside the box for a diverse pool