Reference: 5877 MLR

Job Description:

Data Extraction
Define data requirements that meet the specific needs of a defined business problem
Draw, combine and analyse data from various sources
Report on information retrieved so as to provide insight into business problem and solutions
Use modelling techniques and tools in analysing large and/or complex data sets
Translate, merge, clean and/or map data into conceptual, logical and physical data models
Data and Analytical Presentation
Data presentation designed to demonstrate conclusions gained from analysing data
Research and offer suggestions pro-actively on data and end-result presentation
Develop graphs, reports, and presentations of project results
Perform basic statistical analyses for projects and reports
Create and present quality dashboards
Generate routine and ad hoc report
Data and Analytical Recommendations
Provide insight into business problems with pro-active recommendations on decisions and future analytical projects
Deliver analytical insights to a bigger audience with the intention of driving strategy
Document, implement, maintain and recommend operating methods to improve data processing, distribution, data flow, collection and database procedures
Define future data migration requirements, gathering, validating and documenting data requirements
Identify, develop, and document data standardization, data enrichment operations, data validations, data security requirements, and data exception handling processes

Qualifications:

3 years’ experience in quantitative analytics.
Good understanding of applied statistics and predictive modelling.
Fluency in a programming language (Python, SQL, R, C, Java).
Experience with data visualisation tools (GGplot, Plotly, etc.).
Familiarity with Big Data frameworks (GCP, Hadoop, Spark, Azure).
Experience in retail and credit risk is advantageous.
Bachelor in Business Communication or equivalent in quantitative fields (Statistics, Mathematics, Computer Science, Operations Research, Information Systems).
Course(s) on data profiling and data quality management.
Good problem assessment, decision making, communication, interpersonal skills, self-driven team player who is results driven, strives for excellence and assumes ownership of the given task.
Proficient in SQL or similar programmes
Proficient in MS Word, Excel, and PowerPoint
Programming skills: Adept at queries and report writing. R/Python exposure advantageous
Ability to present complex information in an understandable and compelling manner
Familiarity with basic statistical methods such as linear regression.
Familiarity with visualization methods such as scatter plots, time series plots and the use of percentiles for descriptive analysis
Strong in applied analytics using empirical data to support decision recommendations