Business Intelligence Dev MMH260722-1

Role Purpose

Create and deliver data-driven solutions that add business value through the use of statistical models, machine learning algorithms, data mining and visualisation techniques, Design and maintain enterprise data management frameworks, interpret business requirements into technical requirements, and collaborate with various stakeholders to optimise data utilisation.

Requirements

• 5 - 8 years proven work experience as a Data Architect, Data Scientist, Data Analyst or similar role.
• Exposure and experience with various Databases, Oracle, Structural Query Language server.
• Experience working with Structural Query Language, Python, cloud-based data platforms and a variety of Database software.
• Experience managing/ designing a large data platform and security measures related to Data platforms
• Experience linking business strategy with Data engineering deliverables.
• 5-8 years data analysis experience within an insurance environment.
• Extensive experience with at least one programming language (e.g. Python), business analytics software (e.g. SAS) statistical package (e.g. R) Experience in database language (e.g. SQL)

Duties and Responsibilities

INTERNAL PROCESS

• Identify and develop Predictive and Prescriptive Models to enable better decision making of business.
• Identify, understand and interpret data structures across various databases within the business to facilitate data analysis and continuous monitoring activities.
• Delve for insights in data and processes to help improve the business.
• Contribute to the development of differentiated superior solutions that meet stakeholder and business requirements through analysis business requirements gathering and designs validation.
• Ensure product and/or solution design is congruent with the required business specifications through meeting stakeholder requirements timeously.
• Enable the realisation of the financial business benefits accruing including minimisation of operational costs by ensuring that solutions are implemented effectively.
• Model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.
• Participate and/or lead discovery processes with business stakeholders to identify problems and opportunities that may be addressed with statistical modelling or machine learning.
• Collaborate with business to define approach to resolution of key business problems or development of new business strategies.
• Contribute to the business by highlighting possible opportunities for process improvement and business value creation.
• Identify and develop the hypothesis testing framework and modelling approach to address the business requirements.
• Identify available and relevant data, potentially leveraging new data collection processes such as social media.
• Make strategic recommendations on data collection and experimental design incorporating business requirements and knowledge of best practices.
• Prepare the data for analysis and modelling, which includes data cleaning, standardisation, transformation, dimension reduction and feature engineering.
• Identify and train suitable models/algorithms to discover patterns and make predictions.
• Extend existing code and develop custom code to implement statistical models, machine learning algorithms and data mining techniques for large datasets in a computationally efficient manner.
• Compare model performance, select the best algorithm for the job and be able to motivate this choice in a non-technical manner.
• Interpret results and translate findings into clear and actionable insights that can be easily validated with the project sponsor.
• Communicate findings to business with various skill levels and in various roles, presenting trends, correlations and patterns found in complicated datasets in a manner that clearly and concisely conveys meaningful insights.
• Assist business users in the use of the models and interpretation of model output.
• Assist with monitoring and reporting on model accuracy after it has been embedded in operations.

CLIENT

• Provide authoritative, expertise and advice to clients and stakeholders.Build and maintain relationships with clients and internal and external stakeholders.
• Contribute to the process of negotiating objective and realistic service level agreements, monitor appropriateness and recommend adjustments.
• Define service practices which build rewarding relationships, encourage innovation and allow others to provide exceptional client service.
• Deliver on service level agreements made with clients and internal and external stakeholders in order to ensure that client expectations are managed.
• Make recommendations to improve client service and fair treatment of clients within area of responsibility.
• Participate and contribute to a culture which builds rewarding relationships, facilitates feedback and provides exceptional client service.
• Collaborate with various stakeholders to optimise data utilisation across the business..
• Build and maintain relationships with clients, internal and external stakeholders
• Drive client service delivery goal achievement in line with predefined standards in order to ensure that clients receive appropriate advice and service.

PEOPLE

• Create a positive work climate and culture to energise employees, give meaning to work, minimise work disruption and maximise employee productivity.
• Demonstrate exemplary leadership behaviour, through personal involvement, commitment and dedication in support of organisational values.
• Select and recruit suitably qualified talent in line with Employment Equity principles and business values.
• Drive a culture that guides and directs best practice, fostering an environment of continuous learning, improvement and cohesiveness.
• Enable a learning and growth culture whereby information regarding successes, issues, trends and ideas are actively shared between team members.
• Execute effective workforce planning practices to ensure that staffing requirements are accurately forecasted.
• Identify employee growth and development needs and schedule interventions to enable ongoing development, training and personal growth.
• Effectively manage performance within the team in order to ensure business objectives are achieved .
• Encourage innovation, change agility and collaboration within the teamSupport the building of the team & capability in order to ensure that the team is equipped to strategically partner with business and provide leading solutions.

FINANCE

• Identify solutions to enhance cost effectiveness and increase operational efficiency.
• Manage financial and other company resources under your control with due respect.
• Provide input into the risk identification processes and communicate recommendations in the appropriate forum.
• Escalate unresolved policy and governance compliance issues via appropriate channels for investigation and resolution purposes.
• Implement and provide input into governance processes, systems and legislation within area of specialisation.

PROCESS

• Collaborate with cross-functional teams to design and implement scalable and efficient data architecture solutions tailored to the unique requirements of the business.
• Implement robust security measures to safeguard sensitive data against unauthorised access, breaches, and cyber threats, while adhering to industry-specific security standards and protocols.
• Migrate data from legacy systems to new solutions to optimise new and current database systems.
• Design conceptual and logical data models and flowcharts to improve system performance by conducting tests, troubleshooting, and integrating new elements.
• Define security and backup procedures to comply with cyber security and governance standards.
• Provide operational support for Management Information Systems (MIS) across the business, including establishing data governance frameworks, policies and standards to ensure compliance with regulatory guidelines and industry best practices.
• Identify opportunities to optimise data storage, retrieval, and processing performance through data partitioning, indexing, caching, and other performance tuning techniques.

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