Technology Innovation Opportunities in US Government
Improving the Pipeline
Recruiting technology talent in government is extremely difficult
1. Opportunities are not always obvious
Innovation Teams
Technology Transformation Services (TTS)
Technology Transformation Services
Centers of Excellence
Whole Agency modernization to improve customer experience & reduce legacy IT spending
18F
Project-specific partnerships to define strategies & build solutions, from discovery through acquisition
Presidential Innovation Fellows
Fellowship program where leaders serve a “tour of duty” as entrepreneurs alongside top agency changemakers
Office of Solutions
Portfolio of shared services that help agencies make information accessible, drive innovation, avoid costs
Office of Acquisitions
Buys digital products & services for TTS
US Digital Service
US Digital Service
Coding it Forward
Coding it Forward
Embedded Innovation Teams
Throughout numerous agencies...
...and for small businesses
Recruiting Process
Why it’s hard
2. The hiring process is cumbersome compared to private industry
Hiring Process (example of schedule A-r hiring, remote positions)
HDS* Approval
PD** Identification
VIN*** Requested
Smaller Pool of Candidates Selected
Candidate Interviews
Tentative Offer Drafted & Sent
Hiring Process Begins
At this stage, available funding via project codes are not required to begin the process. However, the contingent approval refers to pending or available project codes which prove 6mos of funding will be available before final approval.
Hiring Office
Recruitment
Pipeline
HR Pipeline
*HDS = Home Duty Station **PD = Position Description ***VIN = Number required to create a position
Job Posted
Contingent Approval
Agency�Pipeline
HDS* Final Approval
Final Approval & Sign HDS*
Candidates Min Qualified
Sign HDS
+
Applicants FWD’d
Candidate Selected
TTS Hiring Timeline
Process Stage | Average Duration |
Application collection | 5 |
TTS application review | 5 |
GSA HR application review | 10 |
30 | |
30 to 60 | |
Total from application to start | 80 to 110 |
...why bother?
Fascinating technology with broad impact
PyGrid
Example technology
25
Traditional Data Flow
model = sm.ols(formula="Size ~ Length*Diameter", data = df).fit()
Scientist Machine
Data Repository
**Results**
26
Pygrid (PySyft) Data Flow
model = sm.ols(formula="Size ~ Length*Diameter", data = df).fit()
Scientist Machine
Data Repository
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**Results**
**Results**
27
PyGrid networks
Census
BLS
NCES
NCHS
BEA
Model Owners Never See Granular Data
28
Amazon
UN
State/Local
NPD
Nielsen
Census
PyGrid networks
Recruiting Process
Potential Improvements
Get early experience with teams, technology
Make current/future technologies obvious!
questions?
Thank you!