Job Description

Empowering Africaxe2x80x99s tomorrow, togetherxe2x80xa6one story at a time.

With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

Job Summary Work collaboratively across the business area to assess the key business challenges that can be solved by data & translate these requirements into data driven solutions for the area. Work on high value & high complexity data science problems & leverage deep data science expertise in advanced statistics, data wrangling, data mining, data analysis, feature engineering &predictive modeling, storytelling, distributed computing & data visualisation, machine learning tools & data intuition to operationalize & continuously improve data solutions that deliver relevant, quality assured, accurate & commercially impactful data to the business.



Data Science

• Develop a deep understanding of the business area and associated challenges
• Cascade business challenges & commercial understanding to the data science team working on data solutions
• Further translate the business challenges into key questions that can be solved with data solutions & coach other data scientists to do the same
• Lead design thinking processes & leverage own deep design thinking skills to determine & confirm hypotheses and priority questions / data challenges & related metrics to be solved for
• Translate vague questions into specific & more tangible data analysis
• Translate this business understanding into data requirements & define a data strategy to deliver against these requirements
• Proactively partner with the data engineering team to refine the data requirements and develop a technical roadmap to deliver raw data to Data Science teams for interpretation & analysis
• Design fit for purpose data interpretation & analysis approaches & create customized data models, algorithms, machine learning tools and recommendation engines to achieve the desired business outcomes
• Use advanced data science skills to mine & interpret data. These include but are not limited to: advanced statistics, data wrangling, data mining, data analysis, feature engineering & predictive modeling, distributed computing, machine learning tools & data intuition
• Leverage the above to analyse & interpret complex data sets & manage large data volumes
• Develop data quality assurance frameworks and tools to test model & analysis techniques (e.g. algorithms, models) & overall data quality
• Apply the testing frameworks to monitor and analyse model performance & data integrity on all data assignments
• Translate analysis (make inferences & reach conclusions) into commercially relevant business insights & leverage storytelling and data visualization techniques to maximize impact & deliver a user friendly product to business
• Consolidate data solutions into viable end products (in the language of business) that can be leveraged on an ongoing basis e.g. dashboards, reports etc.
• Workshop data analysis (trends, insights, forecasts) & findings with business & show tangible business impact to be derived from the data science process
• Regularly refine data analysis based on business inputs leading to the finalization of the data solution
• Provide tangible, practical & commercially viable recommendations to the business based on the outcomes of the analysis & influence business decision making (even if it at times means delivering difficult messages)
• Proactively partner the data engineering teams to assess the effectiveness and accuracy of new data sources & data gathering techniques
• Positively contribute to the data architecture direction by providing expertise on data science tools, techniques and the broader business data requirements
• Promote data literacy across the enterprise by sharing best practices and showing tangible business impact & recommendations as a direct result of the the data solutions provided
• Proactively stay ahead of the curve on data science trends & leading practice data science tools and techniques & transition the organisation to advanced methods for the continuous optimization of data

Risk & Governance

• Identify data risks and mitigate these (pre, during & post solution deployment / data delivery)
• Create business cases & solution specifications for various governance processes (if required)
• Create knowledge & document management processes and practices for data management aligned to Group Risk, Governance & Compliance & Broader Regulatory requirements
• Apply data quality assurance frameworks and tools to guarantee data quality & data integrity (always) across the business area
• Provide risk, governance, compliance & broader regulatory reporting as required
• Contribute to risk, governance, compliance & broader regulatory processes as a data science expert (if & when required)
• Deliver on time & on budget (always)

People

• Coach & mentor other data scientists
• Conduct peer reviews, testing, problem solving within and across the broader team
• Participate as a subject matter expert in the development & development planning of the data science team as required

Education

Bachelor's Degree: Information Technology

Absa Bank Limited is an equal opportunity, affirmative action employer. In compliance with the Employment Equity Act 55 of 1998, preference will be given to suitable candidates from designated groups whose appointments will contribute towards achievement of equitable demographic representation of our workforce profile and add to the diversity of the Bank.

Absa Bank Limited reserves the right not to make an appointment to the post as advertised

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