- Main Purpose of Role
- The incumbent will use their analytical, statistical and programming skills to collect, analyze and interpret large data sets in order to provide insights and data-driven solutions to solve difficult and strategic business [URL Removed] a lesser extent, the incumbent be responsible for developing and deploying new predictive and prescriptive models.
- Required Minimum Education / Training
- Honour’s degree in a mathematical, statistical or actuarial field.
- Required Minimum Work Experience
- 4+ years
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Key Performance Areas
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KPI 1 (Secondary)
Predictive Modelling
- Manage aspects of current scorecards/models.
- Maintain and re-calibrate current scorecards and/or predictive models.
- Develop new predictive models.
- Utilises advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews data results to ensure accuracy; and communicates results and insights to stakeholders.
- Identifies trends, patterns, relationships and discrepancies in data and determines additional data needed to support insight. Processes, cleanses, and verifies the integrity of data used for analysis.
- Identifying, interpreting & explaining the factors giving rise to specific business outcomes.
- Predicting & forecasting probable future business outcomes.
- Identifying key factors of business operations to transform/eliminate/introduce in order to improve business outcome.
- Develop, maintain and refine advanced mathematical and statistical models pertaining to various aspects of the business.
- Apply various supervised and un-supervised learning techniques to various problems.
- Predictive and Prescriptive modelling.
- Solving hard analytical problems for the business.
- Designs various mathematical, statistical, and simulation techniques to large and unstructured data sets in order to answer critical business questions and create predictive solutions which drive improvement in business outcomes.
- Use data profiling and visualization techniques using various tools to understand and explain data characteristics that will inform modelling approaches.
- Mines data using state-of-the-art methods. Enhances data collection procedures to include information that is relevant for building data models.
- Performs data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features.
- Create and deliver business insights.
- Maintain and enhance predictive models currently in production.
- Identify, define and translate business needs/problems into analytical questions.
- Apply statistical and computational methodologies to provide actionable insights and identify opportunities that optimize Gross Profit.
- Assist with the development of scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation.
KPI 2 (Primary)
- Utilises advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews data results to ensure accuracy; and communicates results and insights to stakeholders.
- Identifies trends, patterns, relationships and discrepancies in data and determines additional data needed to support insight. Processes, cleanses, and verifies the integrity of data used for analysis.
- Identifying, interpreting & explaining the factors giving rise to specific business outcomes.
- Predicting & forecasting probable future business outcomes.
- Identifying key factors of business operations to transform/eliminate/introduce in order to improve business outcome.
- Develop, maintain and refine advanced mathematical and statistical models pertaining to various aspects of the business.
- Apply various supervised and un-supervised learning techniques to various problems.
- Predictive and Prescriptive modelling.
- Solving hard analytical problems for the business.
- Designs various mathematical, statistical, and simulation techniques to large and unstructured data sets in order to answer critical business questions and create predictive solutions which drive improvement in business outcomes.
- Use data profiling and visualization techniques using various tools to understand and explain data characteristics that will inform modelling approaches.
- Mines data using state-of-the-art methods. Enhances data collection procedures to include information that is relevant for building data models.
- Performs data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features.
- Create and deliver business insights.
- Maintain and enhance predictive models currently in production.
- Identify, define and translate business needs/problems into analytical questions.
- Apply statistical and computational methodologies to provide actionable insights and identify opportunities that optimize Gross Profit.
-
Assist with the development of scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation.
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Technical
- SAS (Base, Enterprise Guide and Enterprise Miner)
- Python
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Excel
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Behavioral
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Innovative thinking- Deciding and initiating action- Applying expertise and technology- Analysing- Developing results and meeting customer expectations- Coping with pressures and setbacks
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Desirable- Working with people- Adhering to principles and values- Relating and networking- Persuading and influencing- Planning and organizing- Adapting and responding to change
Desired Skills:
- Valuation
- Honours
- 4years
- SAS
- Python
- NPL
- Maths/Stats/Actuary/Quantitative Analyst
Desired Work Experience:
- 5 to 10 years
Desired Qualification Level:
- Honours