About the role

Senior Data Scientist developing predictive models for consumer response to marketing campaigns. Shaping data collection and analysis to validate models in advertising, product innovation, and brand tracking.

Responsibilities

You'd own the modelling approach for one of three domains — Advertising (predicting ad effectiveness), Innovation (forecasting product success), or Tracking (brand health dynamics).
You won't just be handed a dataset and told to find patterns. We're significantly investing in custom-designed surveys built specifically to train these models. You'd be shaping what data we collect, not just how we interpret it.
That means thinking through questions like: What stimulus variations do we need to capture the full distribution of ad quality? How do we ensure proper category and demographic balance? What response patterns actually predict market outcomes? The data asset itself is part of what you're building.
Validation frameworks. We need to know exactly how well our models perform, and more importantly, where they fail. You'd design how we measure this.
Respondent-level synthesis. Most synthetic approaches just predict top-level scores. We're trying to generate full synthetic respondent profiles — hundreds of variables per individual. Architecturally quite different from regression to a mean.
Cold start. How do you predict response to a genuinely novel product category or ad format? Where can we use transfer learning?
Multimodal inputs. Video, images, text, brand context — figuring out what features actually matter for predicting human response.

PhD or equivalent depth in ML, statistics, computational social science, or similar. We want someone who's driven research, not just applied existing tools.
Evidence you can solve problems that don't have existing solutions. Papers, repos, production systems — something that shows how you think.
Interest in experimental design, not just model fitting. If thinking about what data to collect is as interesting to you as what to do with it once you have it, that's a good sign.
Tolerance for messy data. If imperfect real-world data frustrates you more than it energises you, this probably isn't the right role.
Strong fundamentals over framework knowledge. We care more about whether you understand *why* approaches work than which libraries you've used.
Ability to communicate across disciplines. You'll work with research scientists who think in survey methodology terms. Translation skills matter.

Three company-paid mental health days of rest per year (these are pre-scheduled, so the entire company can take the same days off regularly to reset)
Generous PTO policy - Minimum of 20 days of paid time off per year, plus national holidays. Leave over 30 days requires manager and People team approval.
Thoughtfully designed offices to support both individual work and collaboration without interrupting others
Private medical healthcare cover
Medical Aid
Group risk, life & disability contributions
Wellbeing benefits such as free yoga and access to trained therapists / counsellors
Paid 24h secure parking in Cape Town
Free coffee, lunches and in-office snacks
Tailored personal development through training allowances, coaching, mentorship and career frameworks