Experience
- 4–7 years of experience in data science, customer analytics or a closely related quantitative field.
- Demonstrated track record of independently owning and delivering end-to-end analytical or modelling projects.
Qualifications
- Bachelor’s degree in a quantitative discipline such as statistics, mathematics, data science, computer science, engineering or econometrics.
- Postgraduate degree advantageous.
Skills
- Strong proficiency in Python and/or SQL, with experience working with large datasets in production analytical environments.
- Deep grounding in statistics, experimentation and predictive model evaluation, including performance, calibration, stability and business impact measurement.
- Proficiency in supervised machine learning techniques and their responsible application in production.
- Clear, structured communication with technical peers and non-technical stakeholders.
- Demonstrated ability to set and uphold analytical standards and documentation practices.
- AI & data analytics proficiency essential.
Nice to Have
- Experience with call centre analytics, NPS, customer satisfaction measurement or customer journey analysis.
- Experience with alternative data, behavioural signals or unstructured customer feedback, including text analytics or natural language processing.
- Familiarity with South African banking and customer needs across different languages, channels and levels of digital access.
- Exposure to cloud analytics platforms such as Databricks, dashboarding tools and version control such as Git.
- Experience with model governance, independent validation or interpretability methods.
Personal Attributes
- Technically credible and quality-driven, with high standards of analytical rigour.
- Approachable and consultative, providing constructive guidance to junior colleagues.
- Self-directed and dependable, keeping work moving with limited supervision and escalating issues appropriately.
- Collaborative across functions and locations, with integrity and respect for diverse perspectives.
- Pragmatic about trade-offs between rigour and delivery pace, with a focus on measurable customer and business outcomes.
As a Senior Data Scientist supporting Customer Experience at GoTyme Bank South Africa, you will independently own and deliver complex analytical and modelling work that improves customer experience, service performance and customer outcomes. You will work end to end with limited supervision, providing technical expertise across call centre analytics, customer feedback, NPS and alternative data. Alongside delivery, you will provide informal technical coaching to junior colleagues and contribute to analytical standards across the team.
Key Responsibilities
Independent Analytical Delivery
- Own end-to-end delivery of CX analytics projects, from scoping and data preparation through analysis, modelling, validation and stakeholder communication.
- Analyse customer, transactional, call centre and feedback data to identify drivers of satisfaction, contact demand, repeat contacts and resolution outcomes.
- Lead the design, execution and evaluation of experiments and service improvements, including post-implementation reviews and business impact measurement.
- Deliver analysis of Net Promoter Score (NPS), complaints and customer journeys to identify friction and recommend practical improvements.
Modelling and Feature Engineering
- Develop features and model inputs from structured and unstructured data, including interaction records, survey comments and digital behaviour, owning their quality and documentation.
- Lead or contribute significantly to predictive models and text analytics that explain customer sentiment, anticipate service needs and support better customer outcomes.
- Define and maintain monitoring for model and CX performance, including drift, stability, segment differences and data quality.
Standards and Technical Craft
- Set and uphold analytical standards within the CX domain, including code quality, documentation, reproducibility and governance requirements.
- Conduct peer reviews and proactively address risks in analytical methods, data interpretation and responsible use of customer information.
Coaching and Knowledge Sharing
- Provide informal technical coaching and guidance to junior colleagues, helping them develop skills and resolve analytical challenges.
- Share methods, reusable approaches and lessons learned through team forums and Communities of Practice.
Stakeholder Engagement
- Translate complex analytical outputs into clear recommendations for customer experience, call centre, operations and product teams.
- Build effective relationships with business, Data and Engineering teams so that analytical solutions are understood, implemented and used.
Our Benefits Include:
Comprehensive Group Life Cover
- Life Cover
- Funeral Cover
- Global Education Protector
- Disability Cover (incl. Contribution Protector)
- Severe Illness Benefit
Healthcare That Works for You
- Full company contribution to Health Insurance for eligible employees.
- Partial company contribution to Medical Aid options for eligible employees.
Plan for Your Future
- Access to a Retirement Annuity, with convenient payroll deductions to help you save for retirement while benefiting from applicable tax advantages.
Other benefits include:
- EAP support (counselling, financial and legal for you and anyone financially dependent on you).
- Competitive, industry-benchmarked salaries.
- Non-guaranteed performance bonuses.
- Access to company shares (T's & C's apply).
- Wellness days.
- Social clubs.
- On-site barista.
