JOBS: Senior Business Intelligence Analyst at I&M Bank

PURPOSE:

The role is responsible for deploying business intelligence methods for purpose of driving client wallet deepening initiatives.

PRIMARY RESPONSIBILITIES:

The Incumbent will report to the Head of Client Solutions, Personal and Business Banking, and will be responsible for:

• Conduct exploratory data analysis.
• Develop new data sets using feature engineering techniques.
• Transform large, complex datasets into pragmatic actionable insights.
• Leverage data to identify, quantify and influence tangible business gain.
• Demonstrate a strong understanding of agile delivery.
• Implement analytical model designs, perform any restructuring required and review dataset implementations performed by the data engineer and BI developers.
• Select features, building and optimize classifiers using machine learning techniques.
• Data mining using bank-selected data mining tools.
• Enhance data collection procedures to include information that is relevant for building analytic systems.
• Develop and maintain documentation/manuals on models developed, reports generated, and statistical solutions devised.
• Processing, cleansing, and verifying the integrity of data used for advanced analysis.
• Doing ad-hoc analysis and presenting results in reports, dashboards, and charts.
• Creating automated anomaly detection systems, dormancy predictors, and constant tracking of its performance.
• Challenge ideas and methods while working together with talented, highly skilled team members.
• Design, create, interpret and manage large data sets to achieve business goals.
• Design, build and maintain various parts of the data warehousing with respect to requirements gathering, data modeling, metric establishment, reporting production, and data visualization.
• Gather and process raw, unstructured data at scale into a form suitable for analysis then consolidate it into the data warehouse in order to perform business intelligence and advanced analytics.
• Implement statistical data quality procedures or test-driven approach for quality assurance.
• Knowledge of coding principles with pyspark or spark 8 and capability to perform queries, aggregations, joins, and transformations using spark, hive, and pig.
• Deliver value by creating functions, classes, and packages to automate processes and workflows for production deployment.
• Evaluate data sets for accuracy and quality using statistical data quality procedures, software, or test-driven approaches that ensure quality assurance and solve any issues which may arise.
• Improve data foundational procedures, guidelines, and standards and develop best practices for data management, maintenance, reporting, and security.
• Conduct performance tuning to be able to optimize the application of statistical models and scripts.
• Carry out technical user training as required to enable users to interpret data science solutions.
• Ability to take personal responsibility and accountability for timely response to client queries, requests, or needs, working to remove obstacles that may impede execution or overall success.
• Assist in developing and implementing a program of continuous improvement of data processes through a cycle of analysis of existing systems, processes, and tools and identifying areas for improvement and implementing high-impact changes, and getting feedback from stakeholders.
• Understand key performance measures and indicators that drive the company performance measurement, reporting, and analytics across functions and understand how these metrics and measures align and track against overall business strategies, goals, and objectives.
• Work with business customers to understand business requirements and implement solutions and with business owners to develop business questions and to build datasets that answer those questions.
• Assist to analyse use case requirements from BI analysts to determine operational problems, define data modeling requirements, gather and validate information, apply judgment and statistical tests and develop data structures to support the generation of business insights and solutions.

PERSON SPECIFICATIONS

Academic Qualifications

• Bachelor’s degree in a Business related field from a recognized institution.
• Professional training in data science and analytics will be an added advantage.

Experience

• At least 2 years’ relevant experience.

Generic Competencies

• Technical skills;
• Ability to communicate;
• Report writing skills; and
• Numeric skills.

Skills and Attributes

• Knowledgeable in financial analysis;
• Good communication and interpersonal skills; and
• Good credit risk assessment skills.