Head, Data Science at NCBA Group

Job Purpose Statement

Enterprise Data Management ("EDM”) is a process that seeks to ensure Data in NCBA Group PLC is accurate and consistent to meet the strategic and business goals. "EDM" has eight key capabilities i) Data Architecture (DA); ii) Data retention & archiving (DRA); iii) Data quality management (DQM); iv) Metadata management ("MM"); v) Master data Management (MDM); vi) Data privacy & security (DPS) vii) Business Intelligence and Analytics (BIA) and viii) Datagovernance.

The Senior Data Scientist role is:

•  “The Bridge,” closes gaps between data science and business, acting both as a data science visionary and a technical lead for the organisation.
•  Ensure the business creates additional value through the utilization of data assets and analytics.
•  Define best practices for data science processes, from team functional design, problem definition to presentation.
•  Consistently identifying and monitor key business risks and realizing the data needs of the business.
•  Drive experimental data modelling designs within the business.
•  Drive development of effective credit risk management models across the group
•  Guide the professional and technical development of data science capability within the unit
•  Quality leadership that effectively translates to a favourable environment and employee satisfaction.

Ideal Job Specifications
Academic:

•  Bachelor’s degree in Statistics, Data Science, Mathematics, Computer Science or any other related quantitative field. A working experience of the same is also acceptable for the position.

Professional:

•  Big Data or Data Science certification from recognized institutions is a big plus
• Head, Data Science

Desired work experience:

•  At least 6 years of working experience in a data science position.
•  Highly skilled in statistical and modeling packages such as SAS, Matlab, R, Python and other advanced analysis tools.
•  An expert in data management programming such as SQL, PL-SQL as well as being familiar with the workings of motion-tracking data and time-series analyses.
•  Have a proven and successful track record of leading high-performing data science teams, leading through the successful performance of advanced quantitative analyses and statistical modeling that positively impact business performance.