What we do

Slant is a research-led market analytics company that turns real consumer transaction data into intelligence for investors and consumer-facing businesses. Each month we process 250,000 anonymised South African bank accounts - roughly 25 million transactions - covering all major banks. Every transaction is classified against our proprietary brand and retailer taxonomy, giving clients a granular, observed view of how money is actually being spent across the economy. We deliver this through interactive dashboards, bespoke research, and a monthly publication, Currents, that synthesises emerging consumer trends. Our clients include leading retailers, asset managers, and corporate strategy teams.

Why work for us

Slant sits on one of the most distinctive datasets in South African finance: millions of real consumer transactions, updated weekly, spanning every major spending category. You won't be working with surveys or scraped proxies - you'll be building models and products on observed behaviour. As a small, growing team you'll have direct access to leadership, real ownership of what you build, and the ability to see your work shape investment decisions and corporate strategy.

Our culture

We are a small team that values rigour, curiosity, and clear thinking. The work is research-driven - we believe that the quality of insight depends on the depth of engagement with the data. We operate with minimal hierarchy: ideas are tested on merit, feedback is direct, and everyone contributes to the direction of the product. We're looking for people who take ownership and pride in delivering excellence for clients.

Our data process

Our stack is built on Python, SQL, AWS, and BigQuery. The core technical challenge is categorising and enriching millions of raw transactions into structured, brand-level market intelligence - then making that data available to clients through dashboards and research products. We work iteratively, shipping frequently and refining based on what we learn. We're actively expanding our use of ML and LLMs to improve classification, segmentation, and insight generation.

Our hiring process

Our process is straightforward and designed around mutual fit. It typically includes an initial conversation with the founder, a technical assessment relevant to the role, and a team interview. We move quickly and value directness throughout.