Lesaka Technologies is seeking a Data Scientist: Marketing to turn customer and behavioural data into actionable marketing interventions. This is a hands-on role where you’ll combine data science, engineering, and marketing analytics to optimize campaigns and drive measurable business outcomes.

What You’ll Do

• Build and maintain marketing datasets, pipelines, and automation workflows using Google Cloud (Data Fusion, Dataflow, Pub/Sub, BigQuery), with Azure integration where needed.

• Develop segmentation, propensity, churn, and uplift models to identify who to target, what message to send, and through which channel.

• Operationalize models for campaigns across SMS, email, push, USSD, call centre, WhatsApp, and other channels.

• Measure campaign performance and refine models with incrementality testing, A/B experiments, and KPIs.

• Ensure data quality, compliance, and auditability across marketing data.

What Success Looks Like in the First 90 Days

• End-to-end marketing data flow is mapped and understood.

• A production-ready targeting model or baseline scoring approach is live.

• Campaign measurement framework (dashboards, tables, KPIs) is established.

• Data quality risks are documented and mitigated.

Required Skills & Experience

• 3+ years in data science or applied analytics in fintech, banking, telco, retail, or similar customer-scale environments.

• Strong Python and SQL, with experience in BigQuery.

• Experience with supervised learning, segmentation/clustering, uplift or causal models.

• Hands-on experience delivering pipelines on GCP, including batch and streaming workflows.

• Experience integrating Azure Data Factory or mixed-cloud pipelines is a plus.

• Strong engineering mindset: reproducible pipelines, version control, and operational support.

Nice to Have

• Marketing automation or campaign tooling exposure.

• Knowledge of MLOps, model monitoring, and feature stores.

• Experience with identity resolution, customer matching, and fraud/credit signals.

• Familiarity with South African regulatory and privacy requirements.

Personal Traits

• Enjoys turning messy real-world data into actionable insights.

• Comfortable challenging assumptions with evidence.

• Outcome-driven, not just model-driven.