Senior Analyst (Decision Science) at RCS

You will be performing analysis and developing predictive models to optimise risk decisions.

 
What you’ll be doing?

• Performing analysis to determine the impact of strategy changes to areas of application and account management strategies
• Presenting ideas via reports and presentations, outlining findings and making recommendations for improvements to senior stakeholders
• Investigating data integrity issues, test assumptions and validate analytical results, ensuring accuracy and sensitivity of findings
• Using advanced analytical techniques such as modern data mining, pattern matching, data visualisation and predictive modelling tools to produce analyses and algorithms that assist with the business decisions
• Setting up experimental designs to answer key business questions
• Forecasting and monitoring market trends using statistical techniques
• Assisting in implementing strategy changes to live decision systems
• Assisting with Application and Behavioural Scorecard development and testing
• Performing complex statistical analysis to support decision-making and mitigate credit risk
• Working within a team of Risk Analysts on best practice credit risk management principles and statistical analysis

What’s the culture like?

• Passionate | Optimistic | Informed | Uncomplicated

What you’ll need?

• Bachelors Degree or higher in an applicable field of study:
•  For example: Mathematics, Statistics, Economics, Operational Research, Actuarial Science or Finance (CA (SA), CIMA, CFA etc.)
• At least 4 years’ relevant experience:
• in scoring and bad debt provision techniques in consumer lending
• in credit risk analysis on unsecured lending products
• preparing data-driven credit policy recommendations for Senior Management and delivering compelling presentations
• manipulating and analysing data using SAS, SQL, SAS Macros or other data analysis tools for complex modelling purposes or forecasting, i.e. ability to perform statistical analysis on large datasets
• database architecture, i.e. understanding of database and data warehouse concepts and functions
• Strong analytical, problem solving and conceptual thinking skills
• Knowledge of statistical and mathematical models and methodologies
• Ability to explain complex statistical information