Data Analyst

SUMMARY:
Utilize data, machine learning, statistical and mathematical models to solve business problems and enabling the effective use of data by utilizing cutting-edge technologies.

POSITION INFO:

Key Responsibilities:

Build data models to address Group’s business problems

• Provide into the database architecture design, maintenance and optimisation
• Identify areas to increase efficiency and automation of processes
• Contribute to create automated processes to extract, transform and load data
• Build predictive models and machine-learning algorithms.
• Deploy & maintain ML models as APIs for use in live environments
• Combine models through ensemble modelling
• Enhance, find patterns in and build models on large data sets using the appropriate modelling technique and analysis methodologies.
• Apply data mining techniques and perform statistical analysis on large data sets.
• Develop experimental design approaches to validate findings or test hypotheses.
• Perform analysis, interpret and explain results using appropriate statistical tools and techniques translating findings into clear, actionable and timely insights.
• Validate analysis using appropriate techniques i.e. applying test data sets, A/B testing, scenario modelling, etc.
• Productionise models using the company’s standard processes and techniques.
• Monitor the predicted outcomes of models and understand business requirements to ensure that models are delivered in an appropriate format.
• Implement and recalibrate models to enhance and improve prediction and improvement of models to ensure alignment
• Implementation of preventive controls to minimise model risk
• Develop data science products and solutions for the organisation
• Translate meta data into explanatory report and visuals for easy understanding to end user.
• Present the findings and proposals to business users in an understandable format
• Drive continuous improvement of operational reporting processes and policies in support of business objectives and growth.

Undertake and source data collection, pre-processing and analysis for the entire group

• Identify new diverse data sources and automate data sourcing processes with consideration to partner with third party sources.
• Undertake pre-processing of structured and unstructured data.
• Analyse large amounts of information to discover trends and patterns.
• Ensure that the data science and analytics strategy is implemented and that process improvements for data science and analytics activities are identified and actioned.
• Collaborate with the business owners to identify challenges and opportunities, requirements and expected outcomes of modelling to ensure strategic alignment and value creation.
• Collaborate with subject matter experts and data analytics team to select the relevant sources of data and information.
• Partner with the Data Engineering team as necessary to manage data ingestion.

Present embedded analytics in data models to enable quick visualization

• Present business cases around embedded trends to internal business users
• Communicate findings to business by presenting trends, correlations and patterns found in complicated datasets in a clear and concise manner to convert meaningful insights and defend recommendations.
• Generate concise reports with relevant visualisations and commentary for end users in an understandable, timeous and accurate format.
• Ensure full compliance to statutory regulations, policies, procedures, best practice, professional standards as well as the company’s strategy

Ensure data governance and data quality assurance standards are upheld

• Facilitate an understanding of data sources to ensure governance, procedures and standards are upheld.
• Build data quality metrics and conduct data validation testing
• Follow the IT governance process when implementing a change to ensure governance standards and protocols are followed
• Work close with business to understand business processes and standards in order to develop data quality assurance metrics
• Build exception reports to help identify data quality problems
• Provide feedback to business owners on identified problems to ensure quality of data is rectified.

Deal with customers in a customer centric manner

• Implement the policy, procedure and standards for excellence in customer centricity to be applied in the area of responsibility.
• Provide leadership in customer centricity by communicating the intent and strategy for optimisation of customer satisfaction while acting as the champion through example.
• Recognise and celebrate customer centric behaviour within others.
• Manage colleagues and customers’ expectations and communicate appropriately.
• Act in a customer centric manner that is in line with the service code.
• Action errors and concerns raised within 24hrs.

Effective self-management and teamwork.

• Actively and consistently maintain high standards of professionalism in all aspects of personal presentation and delivery.
• Apply knowledge of the organizational systems, structures, policies and procedures to achieve results.
• Demonstrate initiative in follow through to ensure that personal quality and productivity standards are consistently and accurately maintained.
• Provide appropriate resolution for tasks or deadlines not met.
• Support and drive the business’ core values.
• Maintain a positive attitude and respond openly to feedback.
• Take ownership for driving own career development.
• Show commitment to teamwork and a willingness to go the extra mile to achieve team objectives.

Knowledge

• In-depth knowledge and experience of Retail SAP architecture, implementation and operations
• Strong networks and knowledge of emerging trends across Data/Analytics (Big Data, Machine Learning, Deep Learning, AI)
• Expert knowledge of complex IT environments (technical, security, business)
• Knowledge of technology and SDLC and Agile methodology
• Advanced knowledge of compliance and IT governance
• Proven track record of using Python to develop and productionise machine learning models (Ex Scikit-Learn, Tensor flow, H20)
• Data Visualisation Experience
• Experience of AWS and Linux (AWS EC2)
• Experience in applying advanced analytical and statistical methods in retail industry, financial and supply chain industries
• In -depth knowledge of Group IT policies, practices, processes and systems
• Good understanding of the Group’s different business operating models
• Express and implied ethical responsibilities
• Good understanding of the system integrations

Skills

• Project management
• Conflict management
• Stakeholder management
• Writing and Reporting
• Applying Expertise and Knowledge
• Business and Financial acumen
• Data Architecture, Data Modelling and Data Pipelining
• Solutions Architecture
• Model Testing skills
• Interpersonal skills
• Persuading and Influencing skills
• Professional and technical proficiency
• Analysis and Judgment

Behaviours

• Deciding and initiating Action
• Working with People
• Presenting and communicating information
• Learning and Researching
• Planning and Organising
• Delivering results and meeting customer expectations
• Problem solving
• Coping with Pressures and Setbacks
• Entrepreneurial and Commercial Thinking

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