Responsibilities:
- Gather, capture, understand, and communicate requirements for process data analytics (for smart sensor
value-add and process monitoring and diagnosis) - Apply and refine stage-gate approach for process data analytics lifecycle.
- Play a supporting role in identifying potential new process data analytics candidates from literature and
client pain points, supported by appropriate business case - Develop new process data analytics content (hypotheses and proof-of-concept code)
- Package promising process data analytics content for scale (writing robust and scalable content according
to internal best-practices standards, assist software developers with integration of content into analytics
platform) - Evaluate packaged process data analytics performance as applied to client contexts.
- Training of and knowledge transfer to internal and external users of process data analytics
Minimum Requirements: - 3+ years relevant experience in industrial/process data analytics
- Bachelors Degree in Engineering
- Extensive experience in data analytics applied to industrial context.
- Extensive experience in programming (databases, Python [pandas], Jupyter notebooks, version control,
code testing, Agile concepts). - Medically fit must be able to pass medical examinations at mines.
- Excellent communicator and good inter-personal skills, especially in cross-discipline and cross-company
collaborations. - Fluent in English.
Desired Requirements: - Experience with full lifecycle of innovation projects
- Experience in Django, Kubernetes, plotly, Azure DevOps
- Ability to multi-task between several projects at a time
- Post Graduate degree/diploma in data analysis
Desired Skills:
- Engineering
- Data Analytics
About The Employer:
Over the years my client has built a reputation distinguished by signal processing experience, enterprise-level software engineering, and two decades of deep domain expertise within the digital productivity, workplace safety and employee healthcare sectors.