Specialist Data Scientist at Absa South Africa

Job Summary

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 define, build, operationalize & continuously improve data solutions that deliver relevant, quality assured, accurate & commercially impactful data to the business.
Job Description

Data Science

•  Participate in design thinking processes to determine & confirm hypotheses and priority questions / data challenges & related metrics to be solved for
•  Translate business questions to be solved into data requirements & define a data solutions to deliver against these requirements
•  Proactively partner with the data engineering team to refine the data requirements 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
•  Analyse & interpret complex data sets
•  Apply quality assurance frameworks 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
•  Produce business insights and recommendations based on data analysis & modeling concluded & where relevant with knowledge and experience of e.g. Java, Scala, Python, Hadoop, Apache Spark & Kafka
•  Use storytelling and data visualization techniques to maximize impact & deliver a user friendly product to business
•  Contribute to the consolidation of data solutions into viable end products (in the language of business) that can be leveraged on an ongoing basis e.g. dashboards, reports etc.
•  Present data analysis (trends, insights, forecasts) & findings to business & show tangible business impact to be derived from the data science process
•  Facilitate peer reviews & feedback on data solutions
•  Refine data analysis based on business & peer reviews
•  Contribute to the assessments of the effectiveness and accuracy of new data sources & data gathering techniques
•  Promote data literacy with your business stakeholders by sharing best practices and showing tangible business impact & recommendations as a direct result of the the data solutions provided
•  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

Accountability: 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)
•  Apply data quality assurance frameworks and tools to guarantee data quality & data integrity (always) for specific data solutions
•  Contribute to risk, governance, compliance & broader regulatory processes as a data science expert (if & when required)

Accountability: People

•  Coach & mentor other data scientists
•  Conduct peer reviews, testing, problem solving within and across the broader team

Education

Bachelor's Degree: Information Technology (Required), Bachelor's Degree: Statistics (Required)

• 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