Lead Data Scientist
7 days ago
Software development for cloud services and services at the edge. Development and extension of micro-services that facilitate the ease of use of machine learning models in a manufacturing environment. Architecting how the overall solution fits together and optimizing for ease of use, cost and improved quality and functionality over time. Support on model training and system configuration best practices
Job Requirements
- Demonstrated ability to foster an environment for ideation, prototyping and production
- Demonstrated business acumen to take from design to implementation and preferably experience scaling a concept
- Must have IT Development and Systems Knowledge
- Experience with software development methodologies and practices (Agile, Scrum, etc.)
- Experience in Data Analysis and Advanced Proficiency in Microsoft Office suite, including Word, Excel, and Outlook
- Strong Leadership Behaviours with good People Management skills and Problem Solving Skills
- Strong Interpersonal skills to manage relationships with a variety of partners and stakeholders
- Must have an excellent ability to multi-task effectively working on several projects synchronously
- Experience in rolling out initiatives that leverage multiplatform technologies
- Willingness to travel nationally and internationally
- Willingness to work a 3 shift model
- Ability to perform the minimum required physical and mental requirements of the function.
- Leadership behaviours as per LEAD
**Qualifications**:
- Minimum NQF 7 - BSC/BCom/BTech in Information Technology or B. Eng. (Industrial Engineering) or relevant equivalent.
Experience
- Minimum of 5 years’ experience in IT/Manufacturing, or
- At least 6 months participation on our MBSA Graduate Development Programme
Knowledge:
Operating System
- Comfortable in Linux environments, specifically Debian-based, e.g. Ubuntu
- Comfortable developing locally on a Windows machine using WSL2
Programming & Scripting Languages, Version Control, Software
- Strong modern Python knowledge (3.8+); Bash scripting;React & Typescript knowledge beneficial
- Working-level git proficiency
- Understanding of object-oriented programming
- Experience in Test Driven Software Development
- Knowledge of software and business process modelling techniques and tools (e.g. UML)
- Working proficiency of at least the following Python packages - Tensorflow, Keras, MLflow, numpy, asyncio, pytest, pydantic, fastapi, tox, opencv, Pillow, onnx. There are significantly more Python packages in use, but a working knowledge of these will provide the most upfront value.
Automation
- Knowledge of developing and maintaining CI/CD pipelines; container technologies such as Docker; automation in quality assurance, integration and deployment - e.g. developing end-to-end tests that span across docker containers in a CI/CD quality gate in a virtualized environment
Artificial Intelligence, Data and Cloud
- Experience debugging and interpreting the outputs of machine learning models
- Knowledge of labelling best practices to advise annotators when setting up new use cases; Databricks (or similar) for automated cluster management and the use of IPython notebooks for rapid prototyping; cloud design patterns (e.g. hybrid cloud); cloud computing, services and cloud platforms (e.g. Azure); Azure IoT hub & Azure Data Factory would be beneficial; big data technologies (e.g. Hadoop, Hive, Hbase, Spark) and data analytics would be beneficial; descriptive and predictive analytics; designing data warehouses and data lake; data modelling and storage with NoSQL and relational databases (e.g. CouchDB, PostgreSQL); fundamentals and management of databases.
- Technical skills in database and SQL.
Architecture
- Experience developing and maintaining APIs (e.g. REST); systems design, enterprise architecture and development; microservice architecture
Hardware
- Knowledge in technologies like servers, storage and virtualization; IT infrastructure design, deployment and management; high-availability concepts to build robust computing environments; network infrastructure (e.g. switches, routers, firewalls); computing and working with ARM64 devices; CUDA and TensorRT GPU technologies would be beneficial
Working Model
Security
- Knowledge of commercial and open source security tools; computer and network security, authentication and security protocols; IT security architecture; penetration testing techniques and tools.
Customer Support
- Knowledge of help desk and support services; incident and problem management
- Experience with incident systems, ticketing systems (e.g. CISM) and monitoring tools; in providing 24/7 on-call support for high-availability systems; customer relationship management
Outputs
- Liaise directly with various manufacturing plants worldwide to provide product and service support.
- Manage and coordinate system upgrades/bug fixes and support with product testing.
- Ensure to interpret business strategy and determine innovative solutio
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