Data Science Engineer
at ZS Associates
Toronto, ON, Canada -
| Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
|---|---|---|---|---|---|---|---|
| Immediate | 01 Sep, 2024 | Not Specified | 01 Jun, 2024 | N/A | Written Communication,Software Development,It,Pipelines,Design Patterns,Project Teams,Communication Skills,Aws,Scalability,Linux,Data Structures,Computer Science,Shell Scripting,Presentations,Kubernetes,Algorithms,Azure,Docker,Machine Learning | No | No |
Required Visa Status:
| Citizen | GC |
| US Citizen | Student Visa |
| H1B | CPT |
| OPT | H4 Spouse of H1B |
| GC Green Card |
Employment Type:
| Full Time | Part Time |
| Permanent | Independent - 1099 |
| Contract – W2 | C2H Independent |
| C2H W2 | Contract – Corp 2 Corp |
| Contract to Hire – Corp 2 Corp |
Description:
- Toronto, Canada
- Canada
- Insights & Analytics
- Advanced Data Science
- 20319
ZS is a place where passion changes lives. As a management consulting and technology firm focused on transforming global healthcare and beyond, our most valuable asset is our people. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping solutions from start to finish. At ZS, we believe that making an impact demands a different approach; and that’s why here your ideas elevate actions, and here you’ll have the freedom to define your own path and pursue cutting-edge work. We partner collaboratively with our clients to develop products that create value and deliver company results across critical areas of their business including portfolio strategy, customer insights, research and development, operational and technology transformation, marketing strategy and many more. If you dare to think differently, join us, and find a path where your passion can change lives.
How To Apply:
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Responsibilities:
- Build, orchestrate, and monitor model pipelines including feature engineering, inferencing and continuous model training
- Scaling machine learning algorithms to work on massive data sets and strict SLAs
- Build and enhance ML Engineering platforms and components
- Implement ML Ops including model KPI measurements, tracking, data and model drift and model feedback loop
- Write production-ready code that is easily testable, understood by other developers and accounts for edge cases and errors
- Ensure highest quality of deliverables by following architecture/design guidelines, coding best practices, period design/code reviews
- Uses bug tracking, code review, version control and other tools to organize and deliver work
- Participate in scrum calls, and effectively communicate work progress, issues and dependencies
- Consistently contribute to researching and evaluating latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts and creating prototype solutions
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Application Programming / Maintenance
Software Engineering
Graduate
Proficient
1
Toronto, ON, Canada
