Senior Data Scientist

Spane4All; Johannesburg; On-site; ZAR 600 000 - 900 000; Full time

Job summary

A leading analytics firm in Johannesburg is seeking a Senior Data Scientist to innovate in pricing and analytical methodologies. The ideal candidate will have over 5 years of experience in data analytics, strong skills in machine learning and statistical modeling, and an understanding of the Credit Life Cycle. This position offers a full-time role in a dynamic environment focused on leveraging data for business solutions.

Qualifications

• 5+ years' experience within a Data Scientist role focusing on data analytics or modeling.
• Good understanding of the Credit Life Cycle.
• Previous experience within a Pricing or Capital team is advantageous.

Responsibilities

• Plan, build, optimize, and implement innovative pricing and analytical methodologies.
• Ensure ethical usage of information in compliance with privacy standards.
• Analyze data to identify commercialization opportunities.

Skills

Data analytics

Machine learning

Statistical modeling

Python

Data visualization

Predictive modeling

Education

Bachelor's degree in Data Science or relevant field

Tools

SAS

Python libraries

Job description

Senior Data Scientist

Location: Johannesburg | Time Type: Full time | Posted Today | Time Left to Apply: 6 days | End Date: September 11 | Job Requisition ID: R

Job Description

• To plan, build, optimise and implement innovative pricing and analytical methodologies, procedures, products and advanced mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.
• Innovate by finding the best fit solution for the situation such as the flexibility of delivery and customized solutions which result in more efficient outcomes.
• Provide input into localisation of appropriate model building policies, standards, frameworks, and governance process and integration of business modelling and analytics value chain.
• Adhere to model building policies, standards, frameworks, and governance process.
• Ensure own ethical usage of information that complies to restrictions applied for privacy and sensitivity classification.
• Understand and ensure implementation and adherence to Privacy business requirements, legislation and policy.
• Ensure reporting of any Information Privacy Incidents and escape appropriately for resolution of Privacy and Protection Audit Findings, Complaints, Incidents, Investigations and Privacy and Protection Assessments.
• Create delivery plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Analyse available data to identify information commercialisation opportunities that have not been explored to address business needs and revenue options.
• Productionise analytics in the approved FirstRand architecture by translating technical data information into practical business information that addresses identified needs.
• Analyse information requirements, availability and quality of data to feed into management for resolution.
• Contribute to the development of core analytical capabilities or model libraries using advanced statistical, quantitative or econometric techniques and utilise as appropriate.
• Collaborate with numerous departments across the business to aid them in the proper use of data to ensure delivery of desired operational results.
• Participate in relevant project related to the business overall analytical needs and opportunities.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Build models that analyse processes to recommend areas for optimisation to achieve cost savings, revenue generation or efficiency improvements for the business.
• Document and audit relevant processes.
• Document and implement models to address specific business requirements.
• Conduct appropriate manipulation and analysis of data to pro‑actively identify and meet needs of the business for the purpose of future work and to ensure high information‑quality and reliability across the business.
• Apply own understanding of statistical techniques to determine approach to provide input required for decisions and design or evaluation of experiments.
• Apply technical concepts such as (Multivariable Calculus, Linear Algebra etc.) concepts to improve predictive performance or algorithm optimisation in data defined products.
• Implement Machine learning mathematical algorithms and automation techniques using open‑source programming languages such as SAS or Python libraries.
• Utilise advanced Predictive modelling techniques to hold insight into outcomes and future events that confront key assumptions.
• Utilise data to model complex abstractions in machine learning research to enable deep learning.
• Utilise pattern recognition technology to recognise patterns in data and the criteria for use interchangeably with machine learning technology.
• Build and program own statistical model in statistical software for application development to productionise the model into a software application conducted by software developers.
• Conduct Text analytics to examine unstructured data to glean key business insights.
• Understand principles of Data Wrangling to identify and recommend corrective actions for imperfections in data quality.
• Participate in enterprise‑wide high level problem resolution by interacting with relevant engineers and product managers, utilising appropriate methods and decide when approximations make sense.
• Conduct data visualisation to present data, findings and techniques to audiences, both technical and non‑technical in a pictorial or graphical format so it can be easily analyzed utilising principles of visually encoding data and communicating information.
• Maintain ownership of models through regular audits and updates to ensure relevance.
• Plan and perform regular model updates that capture evolving business complexity in current models.
• Challenge current models to ensure relevance and accuracy of outputs.
• Test outputs and accuracy of models to ensure relevance.
• Use data and analytic insights to provide input into improving customer experience through a better understanding of the customers context to identify monetization opportunities and monitoring implementation of business decisions to recommend enhancements utilizing statistical modelling and data analysis.
• Validate, interpret and create reports and presentations for data analytics management and relevant stakeholders.
• Review and assist more junior Quantitative Analysts with processes and models.
• Participate and contribute to a development culture where information regarding successes, issues, trends and ideas are actively shared.
• Build and sustain collaborative working relationships with relevant peers and stakeholders to achieve productivity synergies.
• Participate in specialist communities of practice and contribute positively to own and organisational knowledge improvement.
• Contribute to the development of a budget aligned to operational delivery plans, monitor effectiveness and report on variances.
• Build relationships that allow for the managing of expectations; the sharing of knowledge and diverse insights; and the creation of buy‑in.
• Engage in cross‑functional relationships to obtain and to provide work support.
• Take all necessary actions to ensure compliance with relevant statutory, legislative, policy and governance requirements in area of accountability.
• Ensure implementation of relevant policies, governance and practice standards across the business.
• Maintain expert knowledge on relevant legislative amendments, industry best practices and business's internal compliance procedures and requirements.
• Ensure compliance is adopted in terms of systems and procedures as laid out by business.
• Implement and provide input into the development of governance and compliance procedures and processes within area of specialization and identify risks.
• Determine the business questions that need be answered and determine appropriate analytics models for utilisation.
• Source and prepare relevant data sources for analysis.
• Translate business requirements into tangible models utilizing own understanding of the business value of projects, models and processes.
• Develop and apply analytical algorithms and methods to build, test and implement advanced mathematical models and analytical solutions that address business problem, opportunities and improve business outcomes i.e. reduced risk and costs, increased profitability, optimised efficiency and to facilitate strategic decision‑making.

Additional Requirements

• 5 + years' experience within a Data Scientist Role with particular focus in data analytics or modelling.
• Good understanding of Credit Life Cycle.
• Previous experience within a Pricing or Capital team would be advantageous.