5 Unbelievable Ways You Can Be a Better Data Scientist
1. 5 Unbelievable Ways To Be a Better
Healthcare Data Scientist
Damian Mingle
Chief Data Scientist
2. 11
Overview
• For a Data Scientist, it’s important to dig
into the details of the project before
you start modeling
• A Data Scientist who has the business of
healthcare in mind will attempt to
identify factors that might get in the
way of a successful project
• At different phases of a project there
are differing needs for information, but
once you have moved past data
gathering, a successful Data Scientist’s
objective becomes diving into the
details quickly and at a deep level
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5 Ways to be a better Data Scientist
1. Conduct a Resource Inventory
• Know the in's-and-out's of the available resources for a project
• Realize the important variables such as fixed extracts, access to live data,
warehoused data, and operational data
• Remember to include computing resources such as hardware and software
2. Understand the Requirements,
Assumptions, and Constraints
• Risky assumptions should always
prioritized first
• Watch for data traps
• Consider any and all resources,
and technology constraints
• Think outside the box when it
comes to limitations
4. Five Ways to be a better Data Scientist
3
3. Determine Risk and Contingencies
• Have a backup plan or two in place in the
event unknown issues arise
• Experience suggests there are landmines
around every corner, so plan for
alternatives from the beginning
4. Document Meaning
• Develop a working glossary of relevant
business terminology, it will help keep
you and others on track
• Have Data Science terminology defined
and illustrated with examples, but only
work with the terms that directly relate to
the business problem at hand (use the
KISS strategy)
5. Calculate Costs and Risk
• Compare the associated costs
of the project against the
potential benefits
• Knowing this at the beginning
of the project is clearly more
beneficial to you and the
organization than at the close
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Summary
Key Point: As Data Science matures in terms of the business of healthcare, a
Data Scientist needs to be more aware of assessing the situation, taking an
inventory, learning about the risk and developing contingencies, and
understanding the cost benefits of having a successful Data Science project.
Remember: Not every Data Scientist will take these steps, but then again not
every Data Scientist is highly successful. Like water in the desert----a solid Data
Science methodology is critical to the very survival of the underlying business.
Do not leave your organization thirsty when it needs you most!