Data Scientist

Purpose

Wrangle data, analyse data, develop machine learning models and develop data driven solutions to key stakeholders of business areas. May lead small teams. Advanced competency level demonstrated.

Minimum requirements 

• Degree or relevant qualification with quantitative subjects or relevant professional certification.
• Honors Degree in Data Science, AI or Computer Science, Econometrics or Engineering, Statistics, Actuarial Science or similar professional certification.
• 5 years’ experience in data science or analytics or academic or financial role.
• Knowledge of banking and working domain specific knowledge (e.g. credit, collections, HC or sales) for which problem is being solved.

Main duties

• Stakeholder Engagement and Expectation Management.
• Data wrangling and data preparation.
• Analysis, reporting, data visualisation and communicating results.
• Model monitoring and refinement.
• Change management.
• Data ethics, governance and privacy.
• Mentoring and training.
• Research.
• Treating customers fairly and compliance.
• Management of resources.

Key competencies

• Analytical thinking.
• Coping with Pressures and Setbacks.
• Creating & Innovating.
• Delivering Results and Meeting Customer Expectations.
• Leading and Supervising.
• Planning and Organising.
• Business Acumen.
• Computer programming (and ability to learn relevant computer languages quickly).
• Data visualisation skills.
• Facilitation Skills.
• Financial modelling skills.
• Mathematical modelling.
• MATLAB/Octave and/or Java and/or SAS and/or C and/or C++ and/or TensorFlow and/or AWS and/or NoSQL and/or Hadoop/Hive/Pig and/or Azure and/or Spark and/or Julia and/or Unix Shell or similar.
• Python and/or R or similar.
• Report writing skills.
• SQL Skills.
• Understanding and knowledge of: Business policies and procedures. Legislation.