Over the past 4 years, I’ve been asked many times to describe what we look for in our decision scientists (aka data scientists with optimization and operations research backgrounds or industrial/systems engineers).
naming izhard
The field (and it’s use cases) are growing as data and predictive models make their way into nearly every company. So what should you look for when hiring an engineer to build your routing, scheduling, or matching model?
Here’s our list! Hit us up in the comments with what you think
Technical:
- MS or PhD in Operations Research or a related field
- Experience with integer or constraint programming
- Experience in real-time modeling
- Experience implementing or using meta-heuristics / meta-heuristic tool sets
- Experience using SAT, CP or MIP modeling tools
- Familiarity with software development best practices (e.g. agile methodologies and git workflows)
- Programming experience in Go, Python, Java, or a similar language
- Familiarity with R or Python for analysis
- Knowledge of standard experiment frameworks and statistical tests
Collaboration:
- Excellent communication and interpersonal skills
- Experience guiding stakeholder decisions with data
- Experience communicating results of complex algorithms
- Comfortable working with stakeholders to apply optimization technology to their use case
- Experience breaking down a complex business process
- Willingness to guide KPI definition and output views with stakeholders
Not required, but a plus:
- Remote work experience (our
s are all over!) - Interest in decision diagrams and other optimization techniques
- Experience scaling cloud services