Job Title:  Analyst, Personalisation (Fresher Jobs)

Organisation: Stanbic Bank Uganda Limited

Duty Station:   Kampala, Uganda

About the Company:

Stanbic Bank Uganda Limited is a subsidiary of Stanbic Africa Holdings Limited which is in turn owned by Standard Bank Group Limited (“the Group”), Africa’s leading banking and financial services group. The Standard Bank Group is the leading banking group focused on emerging markets. It is the largest African banking group ranked by assets and earnings. Stanbic Bank Uganda Limited is the largest bank in Uganda by assets and market capitalization. It offers a full range of banking services through two business units; Personal and Business Banking (PBB), and Corporate and Investment Banking (CIB).

Key Duties and Responsibilities:

• Oversee data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyse phenomena. Model complex business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques, working closely with clients, data and technology teams to turn data into critical information used to make sound business decisions. Oversee predictive modelling.

Client

• Oversees business integration through integrating model outputs into end-point production systems, where requirements must be understood and adopted relating to data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.

Data

• Oversees the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Oversees data pre-processing including data manipulation, transformation, normalisation, standardisation, visualisation and derivation of new variables/features. Utilises advanced data analytics and mining techniques to analyse data, assessing data validity and usability; reviews result to ensure accuracy, communicates results and insights to executive leadership.
• Guides and validates the design of various complex mathematical, statistical, and simulation techniques to answer critical business questions and create predictive solutions which drive improvement in business outcomes. Drives analytics and insights within required business unit by developing advanced statistical models and computational algorithms based on business initiatives.
• Codes, tests and maintains scientific models and algorithms; identifies trends, patterns, and discrepancies in data; and determines additional data needed to support insight. Processes, cleanses, and verifies the integrity of data used for analysis.
• Presents results and recommendations to executive leadership and influences future business plans based on insights using excellent communication, presentation and visualization capabilities.
• Supervises and oversees the mining of data using state-of-the-art value extraction methods.
• Enhances data collection procedures to include information that is relevant for building data models.

People

• Liaise and collaborate with the entire Enterprise Data Office, providing support to the entire department for its data science needs. Collaborate with subject matter experts to select the relevant sources of information and translates the business requirements into data mining/science outcomes. Supports an executive leadership by identifying and applying best practices in field of advanced analytics (statistics, operations research, etc.) across the organisation.
• Acts as a subject matter expert from a data science perspective and provides input into all decisions relating to data science and the use thereof. Educate the organisation on data science perspectives on new approaches, such as testing hypotheses and statistical validation of results. Validates and certifies the work of other data scientists and trains team members in statistical models and guides junior colleagues or less experienced staff on projects and drives leading practice.

Product

• Develops, implements, monitors and maintains a comprehensive operational IA plan, rules, methodologies and coding initiatives in order to drive IA for remediation efforts. Develops and co-ordinates a comprehensive strategy for productionalising automation software so that it is accurate and well maintained.

Risk, Regulatory, Prudential & Compliance

• Guides the data management and modelling infrastructure requirements and monitors the implementation thereof through the organisations infrastructure development processes, adherence to the organisations model production processes, including UAT. Ensures adherence to governance processes to manage the ongoing enhancement and maintenance of business rules. Conducts regression testing across all relevant systems as required.

Strategy

• Overseeing activities of the junior team members, ensuring proper execution of their duties and alignment with the organisations vision and objectives. Provide oversights and expertise to the Data Science team. Required to draw performance reports and strategic proposals form his gathered knowledge and analyses results for senior executive leadership.

Technology & Architecture

• Builds machine learning models from and utilises distributed data processing and analysis methodologies. Competent in Machine Learning programming in R or Python, with supplementary still in Matlab, Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka.

Qualifications, Skills and Experience:

• Type of Qualification: First Degree
• Field of Study: Mathematical Sciences

Experience Required

• Personalisation, CHNW
• Personal and Private Banking
• 1-2 years
• Experience with customer insights & analytics environment including translating data into insights and translating the derived insights in to actionable customer conversations delivering both customer and commercial outcomes.
• 3-4 years
• Experience working with analytical solutions and products including quantitative analytics and modelling. Experience working with customer conversation portals
• Additional Information

Behavioural Competencies:

• Articulating Information
• Challenging Ideas
• Checking Things
• Developing Expertise
• Developing Strategies
• Embracing Change
• Establishing Rapport
• Generating Ideas
• Interacting with People
• Interpreting Data
• Making Decisions
• Producing Output

Technical Competencies:

• Risk Reporting
• Risk Response Strategy
• Risk/ Reward Thinking
• Verbal Communication
• Write Effective Communications