Vacancies

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The Risk Analyst is responsible for assessing and managing risks associated with retail banking products such as credit cards, personal loans, mortgages, and other consumer lending products. This role involves analyzing customer credit risk, monitoring portfolio performance, and developing risk strategies to optimize profitability while maintaining regulatory compliance.

• Risk Assessment & Analysis: Evaluate customer creditworthiness using financial data, credit scores, and risk models.
• Portfolio Monitoring: Track key risk metrics (e.g., delinquency rates, charge-offs, and loss rates) and identify emerging risks in retail lending portfolios.
• Modeling & Forecasting: Utilize statistical models (e.g., logistic regression, decision trees) to predict default probabilities and optimize risk strategies.
• Regulatory Compliance: Ensure adherence to Basel III, IFRS 9, and other risk governance frameworks.
• Strategy Development: Design risk mitigation strategies, including credit policy adjustments and fraud prevention measures.
• Stakeholder Collaboration: Work closely with credit risk teams, finance, and business units to align risk management with business objectives.
• Reporting & Visualization: Develop dashboards and reports using tools like SAS, SQL, Python, Tableau, or Power BI to provide insights on risk trends.

• Education: Bachelor’s or master’s degree in finance, Statistics, Mathematics, Economics, or a related field.
• Technical Skills: Proficiency in SQL, Python, SAS, or other data analysis tools.
• Analytical Skills: Strong ability to interpret data, identify trends, and develop risk mitigation strategies.
• Financial Knowledge: Understanding of retail banking products, credit risk models, and key performance indicators (KPIs).
• Regulatory Knowledge: Familiarity with Basel III, IFRS 9, stress testing, and other financial risk regulations.
• Communication Skills: Ability to present insights and recommendations to senior management.

• Experience in a financial institution or credit risk role.
• Knowledge of machine learning techniques for risk modeling.
• Experience with data visualization tools like Tableau or Power BI.

  Job Description:

• Analyze large, complex datasets to identify trends, patterns, and relationships that provide actionable insights for business decision-making.
• Develop and implement machine learning models and algorithms to solve specific business problems, such as predictive analytics, classification, clustering, and recommendation systems.
• Clean, preprocess, and manipulate data to ensure accuracy, completeness, and consistency for analysis.
• Collaborate with cross-functional teams, including business stakeholders, data engineers, and software developers, to understand project requirements and deliver solutions that meet business objectives.
• Communicate findings and insights effectively to non-technical stakeholders through visualizations, reports, and presentations.
• Stay current with industry trends, emerging technologies, and best practices in data science and machine learning.
• Participate in continuous learning and skill development to enhance technical expertise and proficiency in data science tools and techniques.

Requirements:

• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, or related field.
• Proven experience in data analysis, statistical modeling, and machine learning techniques.
• Proficiency in programming languages such as Python, R, or SQL for data manipulation, analysis, and modeling.
• Familiarity with data visualization tools and libraries such as matplotlib, seaborn, ggplot, or Tableau.
• Strong problem-solving skills and ability to think critically and analytically.
• Excellent communication skills with the ability to convey technical concepts to non-technical stakeholders.
• Experience working with big data technologies and platforms such as Hadoop, Spark, or AWS is a plus.
• Certifications in data science, machine learning, or related fields are desirable but not required.

Job Description:

• Collaborate with clients to understand their business goals, challenges, and data-related needs.
• Assess the organization's existing data infrastructure, processes, and systems to identify opportunities for improvement and optimization.
• Design and implement data strategies, solutions, and initiatives to address specific business requirements and objectives.
• Develop data models, algorithms, and analytical frameworks to extract insights and patterns from large datasets.
• Provide expertise and guidance on data governance, quality assurance, and compliance to ensure data integrity and security.
• Lead data-related projects, from requirements gathering and solution design to implementation and deployment.
• Conduct data analysis, visualization, and reporting to communicate findings and recommendations to stakeholders.
• Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to drive data-driven decision-making.
• Stay current with industry trends, emerging technologies, and best practices in data management, analytics, and visualization.
• Provide training, coaching, and mentoring to internal teams to build data literacy and capabilities within the organization.
• Serve as a trusted advisor and thought leader on data-related matters, contributing to the overall success and growth of the organization.

Requirements:

• Bachelor's or Master's degree in a relevant field such as Computer Science, Statistics, Mathematics, Business Administration, or related field.
• Proven experience in data analysis, data management, and data visualization, preferably in a consulting or advisory role.
• Strong analytical and problem-solving skills, with the ability to translate business requirements into actionable insights and solutions.
• Proficiency in programming languages such as Python, R, SQL, or other data analysis tools and platforms.
• Experience with data visualization tools and techniques, such as Tableau, Power BI, or matplotlib.
• Excellent communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
• Strong project management skills, with the ability to manage multiple projects simultaneously and deliver results within scope, budget, and timeline.
• Knowledge of data governance, regulatory compliance, and industry standards (e.g., GDPR, HIPAA) is a plus.
• Certifications in data management, analytics, or related fields are desirable but not required.

Job Description:

• Utilize SAS, SQL, Python, Tableau, and Power BI to analyze marketing data and extract actionable insights to drive marketing strategies and campaigns.
• Collaborate with cross-functional teams to develop and execute marketing campaigns that align with business goals and objectives.
• Conduct data analysis and segmentation to identify target audiences, market trends, and opportunities for growth.
• Develop predictive models and machine learning algorithms to forecast customer behavior, optimize marketing ROI, and personalize marketing messages.
• Design and implement A/B tests and experiments to evaluate the effectiveness of marketing initiatives and refine strategies accordingly.
• Create dashboards and reports using Tableau and Power BI to visualize marketing performance metrics, track key performance indicators (KPIs), and communicate results to stakeholders.
• Optimize marketing campaigns through data-driven decision-making, including campaign targeting, messaging, timing, and budget allocation.
• Perform ad-hoc analysis and provide insights on marketing attribution, customer journey mapping, and lifetime value analysis.
• Monitor and analyze digital marketing channels such as email, social media, paid advertising, and website traffic to measure effectiveness and identify areas for optimization.
• Stay updated on industry trends, best practices, and emerging technologies in marketing analytics and data science.
• Collaborate with data engineers and IT teams to ensure data quality, integrity, and accessibility for marketing analytics initiatives.

Requirements:

• Bachelor's or Master's degree in Marketing, Business Administration, Statistics, Computer Science, or related field.
• Proven experience in marketing analytics, data analysis, and campaign optimization.
• Proficiency in SAS, SQL, Python, Tableau, and Power BI for data manipulation, analysis, visualization, and reporting.
• Strong analytical and problem-solving skills, with the ability to translate data into actionable insights and recommendations.
• Experience with machine learning techniques, predictive modeling, and statistical analysis.
• Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Ability to work effectively in a fast-paced, collaborative environment and manage multiple projects simultaneously.
• Knowledge of digital marketing channels, advertising platforms, and customer relationship management (CRM) systems is a plus.
• Certifications in data analytics, marketing analytics, or related fields are desirable but not required.