Description
Job Title: Senior Associate Model Implementation & Data Management
Location: Abu Dhabi
Role Purpose
- The role requires very strong technical and communication skills.
- Manage risk data including data capturing, organizing, storing and analyzing for development, validation and implementation of Risk Rating Models and Scorecards.
- Conduct risk analytics and generate comprehensive risk reports.
- Provide advanced quantitative analytics support to the overall Risk Management function.
- Formulating management techniques for quality data collection to ensure adequacy, accuracy and legitimacy of data.
- Engaging in Risk Architecture projects including implementation of various risk IT applications, data analytics, data flows, standards and processes.
- Strong knowledge of Information Technology systems, Risk Management systems, tools, applications and relational database management systems. Software development and ability to code.
- Develop and implement AI analytics to analyze risk data. Use machine learning techniques to identify patterns, trends and potential risks, including exploration, data analysis and data quality and trend assessment.
- Design data tracking and monitoring tools. Analyze and validate data ensuring data security.
- Ensure all data management and AI analytics practices comply with relevant regulations and organizational policies.
Key accountabilities / responsibilities
- Manage and maintain data for risk models implementation and scorecards development.
- Oversee Credit Risk management processes including Basel II and IFRS9 compliance.
- Conduct risk analytics and generate comprehensive risk reports.
- Utilize statistical tools such as SAS, R and Python for data analysis and model development.
- Write advanced SQL queries to extract, manipulate and analyze data.
- Develop and implement data science, machine learning and artificial intelligence solutions to enhance risk management processes.
- Apply techniques such as generative AI, classification, regression, clustering and other related methods.
- Collaborate with cross-functional teams to ensure data integrity and accuracy.
- Communicate findings and insights effectively to stakeholders.
- Foster a collaborative and team-oriented work environment.
- Stay updated with industry trends and advancements in AI and data analytics.
- Continuously seek opportunities to enhance risk management processes.
Education and experience
- Minimum 3 years of total experience in handling data management projects, data science, machine learning, model development within banking and finance sector, preferably in Credit Risk domain i.e., Basel II and IFRS 9 Risk models development and implementation, risk analytics reporting.
- Bachelors degree in Computer Science, Engineering, Information Systems or a related field.
- Masters degree is preferred.
Specialist skills / technical knowledge required for this role
- Experience working with large and complex data sets including alternative data (bureau, open banking etc.) for credit models.
- Experience in Credit Risk modelling and Risk analytics preferred.
- Experience with data science, machine learning and artificial intelligence techniques including generative AI, classification, regression and clustering.
- Possess strong quantitative skills and solid experience in developing, validating and monitoring risk models. Knowledge of the credit scoring systems available in the market and their use.
- Advanced user of statistical software (such as SAS and R or Python and SQL).
- Good knowledge of handling Risk Technologies & its implementation.
- Ability to work independently on multiple tasks and/or projects.
- Excellent oral and written communication skills in English.
- Proficiency in risk concepts, banking products/operations/systems, pertinent regulatory requirements.
- Flexible team player and able to work and deliver under pressure.
Required Experience
Senior IC