Are you a Data Science Enthusiast with a Passion for Mining and Mineral Processing? Then we’d love to speak to you!
Our Client, a large multi-national is a pioneering company at the forefront of revolutionizing data science within the mining and mineral processing industry. Their client-centric approach drives them to constantly innovate and seek dynamic individuals who are motivated to make a difference. If you’re ready to be part of a cutting-edge team, then this opportunity is for you.
Key Responsibilities
- Complete Functional Specification & Documentation: Lead the creation of functional specifications and documentation for remote monitoring systems.
- Scope Development & Data Requirements: Assist in developing scopes of work and minimum data requirements for implementing remote monitoring systems at new client sites.
- Hybrid Data Processing & Storage: Develop a hybrid data processing and storage system capable of local processing on site and transmission to the cloud for additional processing.
- System Launch & Modular Approach: Lead the launch of monitoring systems with a modular approach for services, actively seeking feedback from users.
- Data Integration & Insights: Integrate data between on-site monitoring systems and the ERP system to provide logistics and service improvement insights.
- Maintenance Scheduling & Calibration: Develop a maintenance scheduling module using ERP data and calibrate the system with clients for accuracy.
- Customization & Adaptation: Customize and adapt developed modules to client-specific data as needed.
- Data Analysis & Interpretation: Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large datasets for various clients and equipment.
- Dashboard Creation & Enhancement: Create comprehensive and meaningful dashboards, maintaining and enhancing existing dashboards and data insights.
- Actionable Insights: Translate visualizations into actionable processes and efficiencies, articulating technical information to relevant clients.
- Advanced ML/AI Outcomes: Deliver data outcomes, from analysis to technical and business intelligence insights, to predictive and advanced ML/AI outcomes.
- Client Collaboration & Reporting: Collaborate with clients to ensure understanding of requirements, devising effective resolutions through innovative data solutions or methodologies. Report findings and recommendations to clients, ensuring relevance and value.
- Leadership & Influence: Influence and lead conversations with clients through quantitative mechanisms.
- Capability Enhancement: Manage, build, and improve reporting, analytics, and data exploration capabilities, collaborating with employees from different departments to enhance data analysis and insights.
Requirements
Qualifications / Exprience:
- Degree: Metallurgical Engineering OR Data Science with a strong background and exprience in the Mining / Minerals Processing Indsutry.
- 1-3 years’ experience within a similar role (Data Science within the Mining / Minerals Processing Industry)
- Knowledge in plant signals and systems modeling and interpretation
- High level of computer literacy
- Knowledge of Machine Learning and Artificial Intelligence concepts and algorithms, with application experience and ideally, understanding of deployment of Machine Learning algorithms (beneficial)
- Proficiency in programming (C#, C++, Python, Java, or R)
- Competency in database query languages (SQL, PostgreSQL)
- Experience with Microsoft Power BI
- Familiarity with relational and time scale databases
- Basic understanding of web technology stack (front-end and back-end) is beneficial but not required
We’ll also be looking for:
- Ability to analyze large data sets
- Proficient in writing comprehensive reports
- Excellent technical aptitude
- Strong verbal and written communication skills
- Creative approach for generating new ideas
- Effective prioritization and planning abilities
- Experience in using cloud services, preferably certified in Azure or AWS
- Own transport and valid driver’s license
Desired Skills:
- Data Cleansing
- Data Mining
- Data Quality
- Data analysis