Data Scientist, IOC - Delmas at Exxaro Resources

PURPOSE:

• Develop and lead the application of data science modelling at an Integrated Operations Centre level to deliver insight-driven tactical and strategic value creation.
• Provide statistical analysis, forecasting, predictive modelling, prescriptive analytics, simulation and optimisation to discover trends, opportunities and threats.
• Design quantitative advanced analytics models that answer business questions and/or discover opportunities for improvement/optimisation at the business unit.
• Use data to support and optimise decision making, including predictive decision-making across the business value chain from the pit right through to the port.
• Ensure the availability of approved resources (skills, funding, technology, etc.) for modelling initiatives, driving change and influencing a wide range of stakeholders.
• Communicate and present findings and recommendations to management and business.
• May coach junior data scientists.

Minimum Requirements    

QUALIFICATIONS:

• BEng Engineering (Relevant) (Essential/Minimum or)B Degree (Relevant) (Essential/Minimum)

EXPERIENCE: 

• 3-5 years Relevant practical or commercial analytics with coding experience in mining or related environments. Technical expertise in ML languages, packages and techniques. A proven track record of successfully leading business integration projects in the fields of data science and machine learning. Sound people and relationship skills that foster collaboration, project management, communication and teamwork. (Essential/Minimum)   Operational

REQUIREMENTS:

• Psychometric Assessment (Essential/Minimum)Certificate of Fitness (Essential/Minimum)

Duties & Responsibilities    

• Best Practice and Knowledge Management    
• Intellectual property management and protection
• Create and manage professional networks
• Participate in tertiary educational relationships
• Participate in professional external forums
• Continuously monitors exchange and preservation of information between operations and individuals to facilitate effective knowledge management
• Stay abreast with advances in field of business improvement, data science and innovation
• Business Performance and Continuous Improvement    
• Monitor Value Chain throughput and identify Improvement opportunities
• Analyse data captured in the Integrated Operations Centre (IOC) to understand the dynamics and variability within the value chain and identify process bottlenecks
• Collect, organise (clean and transform) and analyse data using a broad set of analytical tools and techniques to develop quantitative and qualitative business insights and present these to relevant stakeholders towards influencing improvement, optimisation and prediction across the Business Unit (BU) value chain
• Create new insights from predictive statistical modelling activities that target and deliver value
• Business Review Process    
• Support the business review process by evaluating critical performance areas - 6 monthly, quarterly and monthly within operational function level (mining, beneficiation, engineering etc. or for a smaller business unit)
• Implement and track metrics to enable measurement of process efficiency and effectiveness; auditing of current processes and identification of areas of opportunity
• Compliance, Governance and Assurance    
• Execute responsibilities in accordance to relevant governance, policies and procedures
• In preparing and building data science models: follow a structured and approved process and follow the Information Management (IM) governance in deploying and industrialising models
• Responsible for safe keeping and tracking of all relevant documentation

Customer and Client Relationship Management    

• Establish and maintain key relationships with stakeholders
• Collaborate and communicate effectively with stakeholders
• Provide relevant and specialised support to stakeholders
• Key stakeholders for this role including IOC team members; Digital Value Chain Leads (DVCL), Lead Value Chain Integrator, Business Improvement, Centralised Data Scientists/Principal Industrial Engineer, Data owners and technicians, IM, BU Production Team
• Maintain extensive internal and external professional networks
• Data analytics and business insights    
• Use analytic techniques to understand the dynamics and variability within the value chain and identify process bottlenecks
• Collect, organise (clean and transform) and analyse data using a broad set of analytical tools and techniques to develop quantitative and qualitative business insights and present these to relevant stakeholders towards influencing improvement, optimisation and prediction across the Business Unit value chain
• Create new insights from predictive statistical modelling activities that target and deliver value
• Work closely with business stakeholders (IOC team, Business Improvement and DVCL) to identify value and business needs and translate them into concrete problem statements to deliver on
• Where applicable delivery may require the inclusion/handover to project-based data scientists
• In preparing and building data science models: follow a structured and approved process
• Leverage the appropriate teams to clean and transform data when necessary
• Follow the IM governance in deploying and industrialising models
• Monitor and follow-up on built models when in production to ensure good performance & value creation and update as appropriate
• Strive to align focus to Top 5 and P75 and inversely use analytic insights to influence direction setting in these processes
• Play a role in guiding focus areas for digitalisation
• Be competent in working with any type of data — both structured and unstructured
• Understand when a problem is a data science problem
• Document and maintain an understanding and representation of the BU data landscape
• Establish data requirements around value chain problems and where data gaps exist, work with technicians and data owners to close gaps
• Utilise appropriate indicator/value models for data science initiatives for the purposes of prioritisation and benefit tracking, in collaboration with Business Improvement and Value Chain Integrators
• Create frameworks to measure success, partner with Value Chain Integrator’s to define success metrics, create approaches to track the data and troubleshoot errors, quantify and evaluate the data, then develop a common language and effective visualisation for all colleagues to understand these Key Performance Indicators (KPIs)
• Operationalize data processes - provide the team with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state of the business
• Develop and disseminate models according to an agile (MVP) approach
• Visually represent models in a compelling story
• Identify and build the right user experience so that the output of data science/machine learning workflows is easily interpretable for and actionable by the business users
• Actively participate in cross BU Communities of Practice (CoPs) and Forums to build skill, synergies and scaling

Safe and Healthy Work Environment    

• Establish and maintain a healthy environment and safe operations Practices throughout the Market to Resource value chain
• Ensure compliance with all applicable Safety Health and Environmental (SHE) policies and procedures in line with set standards
• Encourage a culture that focuses on SHE in all operations
• Set design standards in accordance with safe work principles
• Promote adherence to all SHE practices and promote good housekeeping on an ongoing basis
• Address all unsafe practices and potential hazardous situations, rectify and report to superior
• Comply with SHE requirements at all times