| Data Scientist |
Data Scientist - 20hrs/week for the remainder of the year (9 months). They are defining the role to work with the other DS's out in the business to help them adopt SageMaker. Probably won't be the typical Data Scientist assignment, it will help with best practices, adoption, removing roadblocks,etc.
A lot of Data Scientists today are working directly on their laptops in Jupiter Labs or what have you and Nissan is migrating to the platform that is AWS Native (SageMaker) to develop the Client Ops pipeline. That first hurdle is going to be changing their ways of working (porting code, setting up domains, etc…). That's the transition early on. They have Supply Chain, Manufacturing, Marketing and Sales, Total Customer Satisfaction, HR - all of them will have to do a wash, rinse, repeat for each of those groups. Their tactical teams will need help with that transition.
- Most meetings are w/ the Data Scientist in those individual groups, not necessarily the business.
- Meet w/ Cloud Engineers who can set up new domains & provisioning for the different business units.
Skill Set
- SageMaker and setting up those types of pipelines and environments. Someone that has done that transition where they can work on their laptop, but spent the majority of Enterprise Data Science work in SageMaker itself. If there are other features that they aren't leveraging, this person can make recommendations.
- Python is preferred - SageMaker and AWS in general has better support for Python than it does for R.
Timeframe: SOW delivered by
6-1-2023 to Jana Groner Skopec
Interview Process: Interview with Joe, BJ McGovern and a Data Scientist from one of the business units.
Hours: 20 hours per week, for 9 months. A schedule will be established with expected outcomes.
SOW Format: Time & Expense
Location: Remote
