Lead Data Scientist at Absa South Africa

Job Description

Data Science

• Short-term insurance background advantageous. 5 years+ experience. Statistical or Actuarial background. Completed BSc Actuarial Science or BSc Mathematical Statistics minimum.
•  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