Specialist Data Scientist - Secured Lending (AVAF) 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

BRIEF OVERVIEW OF THE SPECIFIC BUSINESS UNIT:

• Absa Vehicle and Asset Finance has been on a healthy growth trajectory to reclaim its leadership spot in the vehicle finance space. The analytics team, working alongside strategy, has been playing an active role in shaping the how of bringing this possibility to life.
• The team is currently engaged in several initiatives in the exploratory and advanced analytics space, to leverage the data that our engineering team has worked tirelessly to store in an easier to access format – hence enabling you to do what you do best!

BRIEF OVERVIEW OF THE ROLE:

• We are pleased to be bringing to the market this exciting role that will work on our vast data assets to unearth insights that will play an active role in shaping the business’ strategy and tactical planning / execution. This will include applying techniques in data wrangling, exploratory analytics and machine learning and AI to solve business problems in the vehicle finance space.
• While we have a healthy book of work and plenty of problems to intellectually challenge our newest team member, we maintain much-needed flexibility for analysts to take on projects that they identify in the business as well!

KEY RESPONSIBILITIES:

• 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. Python, R, Hadoop & Apache Spark
• 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: People

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

MINIMUM REQUIREMENTS:

• Bachelor (Honours) degree in Statistics, Mathematics, Engineering, Physics
• 5 years’ postgraduate work experience in an analytics or data science role
• Expert knowledge of an advanced analytics tool: Python, R, Apache Spark
• Expert knowledge of a data query tool: SQL, SAS
• Expert knowledge of a visualization tool: PowerBI, Tableau

Education

• Bachelor's Degree: Mathematics (Required), Bachelor's Degree: Statistics

Closing Date: 19th, April 2022