Manager, Personalisation Quant Analytics
2025-08-17T18:57:33+00:00
Standard Bank
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https://www.standardbank.com/
FULL_TIME
Kampala, Hannington Road
Kampala
00256
Uganda
Banking
Computer & IT
2025-08-29T17:00:00+00:00
Uganda
8
Job Description
Apply 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. Execute intelligent automation and predictive modelling.
- 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.
- Provides input into Data management and modelling infrastructure requirements and adheres to the organisations infrastructure development processes, including the management of User Acceptance Testing (UAT). Conducts regression testing across all relevant systems as required.
- Ensure 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.
- 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. Ensure ongoing knowledge of industry standards as well as best practice and identify gaps between these definitions/data elements and organisation data elements/definitions.
- Directs the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Performs 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 data results to ensure accuracy and communicates results to Stakeholders.
Qualifications
- First Degree in Information Technology, Information studies or related from a recognised Institution
- Post Graduate Degree in Information Technology, Information studies is preferred.
- Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTML
- 1-2 years proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products, experience in technical business intelligence. Knowledge of IT infrastructure and data principles project management experience. Exposure to governance and regulatory matters as it relates to data. Experience in building models (credit scoring, propensity models, churn, etc.).
- 3-5 years experience working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data.
Additional Information
Technical Competencies:
- Data Analysis
- Data Integrity
- Database Administration
- Diagramming & Modelling
- Research and Information Gathering
- Knowledge Classification
Behavioural Competencies:
- Articulating Information
- Directing People
- Documenting Facts
- Embracing Change
- Establishing Rapport
- Interacting with People
- Making Decisions
- Managing Tasks
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. Provides input into Data management and modelling infrastructure requirements and adheres to the organisations infrastructure development processes, including the management of User Acceptance Testing (UAT). Conducts regression testing across all relevant systems as required. Ensure 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. 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. Ensure ongoing knowledge of industry standards as well as best practice and identify gaps between these definitions/data elements and organisation data elements/definitions. Directs the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Performs 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 data results to ensure accuracy and communicates results to Stakeholders.
First Degree in Information Technology, Information studies or related from a recognised Institution Post Graduate Degree in Information Technology, Information studies is preferred. Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTML 1-2 years proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products, experience in technical business intelligence. Knowledge of IT infrastructure and data principles project management experience. Exposure to governance and regulatory matters as it relates to data. Experience in building models (credit scoring, propensity models, churn, etc.). 3-5 years experience working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data.
JOB-68a2261d49b66
Vacancy title:
Manager, Personalisation Quant Analytics
[Type: FULL_TIME, Industry: Banking, Category: Computer & IT]
Jobs at:
Standard Bank
Deadline of this Job:
Friday, August 29 2025
Duty Station:
Kampala, Hannington Road | Kampala | Uganda
Summary
Date Posted: Sunday, August 17 2025, Base Salary: Not Disclosed
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JOB DETAILS:
Job Description
Apply 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. Execute intelligent automation and predictive modelling.
- 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.
- Provides input into Data management and modelling infrastructure requirements and adheres to the organisations infrastructure development processes, including the management of User Acceptance Testing (UAT). Conducts regression testing across all relevant systems as required.
- Ensure 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.
- 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. Ensure ongoing knowledge of industry standards as well as best practice and identify gaps between these definitions/data elements and organisation data elements/definitions.
- Directs the gathering of data for use in Data Science models, ensuring that chosen datasets best reflect the organisations goals. Performs 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 data results to ensure accuracy and communicates results to Stakeholders.
Qualifications
- First Degree in Information Technology, Information studies or related from a recognised Institution
- Post Graduate Degree in Information Technology, Information studies is preferred.
- Proficiency in application and web development. Structured and Unstructured Query languages e.g. SQL, Qlikview; Tableau; SSIS SSRS, Python JSON , C#, Java, C++, HTML
- 1-2 years proven development experience in software and software engineering. Understanding of financial services data processes, systems, and products, experience in technical business intelligence. Knowledge of IT infrastructure and data principles project management experience. Exposure to governance and regulatory matters as it relates to data. Experience in building models (credit scoring, propensity models, churn, etc.).
- 3-5 years experience working with unstructured data (e.g. Streams, images) Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data.
Additional Information
Technical Competencies:
- Data Analysis
- Data Integrity
- Database Administration
- Diagramming & Modelling
- Research and Information Gathering
- Knowledge Classification
Behavioural Competencies:
- Articulating Information
- Directing People
- Documenting Facts
- Embracing Change
- Establishing Rapport
- Interacting with People
- Making Decisions
- Managing Tasks
Work Hours: 8
Experience in Months: 12
Level of Education: bachelor degree
Job application procedure
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