Data Scientist at NCBA Group

The Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and through the use of advanced statistical

analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.

Academic:

1. Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine
2. Learning, Economics, or any other related quantitative field. Working experience of the equivalent is also acceptable for this position.

Professional:

Big Data or Data Science certification from recognized institutions

Desired work experience:

• At least 3 years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting, preferably working as support data scientist junior support personnel
• Experience working in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, decision tress, and so forth.
• Experience as well as in depth knowledge of the Python programming language, SAS Enterprise Miner and substantial knowledge of big data platforms such as Aster and Hadoop.

Responsibilities

The Data Scientist also plays a leading role in the management of:

• Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations
•  Build the foundation of state-of-the-art scientific and technical capabilities within the Data Science department in order to support several planned and ongoing data analytics projects.
•  Provide forward-thinking recommendations to the business by building in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs
•  Execute ad-hoc data mining and exploratory statistics tasks on large data-sets related to the business 'strategies.
•  Generate actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and datamining
•  Collaborate with senior data scientists to communicate obstacles and findings to relevant stakeholders in an effort to improve decision-making and drive business performance.