🚀 We’re Hiring: Lead Data Scientist

📍 Location: Johannesburg 
🏢 Business Unit: Merchant Operations Division
🧩 Function: Merchant Data Department
👤 Reports to: Executive Head of Data

⭐ Role Purpose

The Lead Data Scientist is responsible for establishing and leading advanced analytics and data science capability within the Merchant Data Department — designing and delivering scalable AI, machine learning, and statistical modelling solutions that drive competitive advantage.

This role acts as a founding practitioner, combining deep technical expertise with business engagement and mentorship to embed data‑driven decision‑making across lending, payments, risk, fraud, and customer experience. The incumbent shapes the technical roadmap, builds experimentation and MLOps foundations, and ensures analytics translate into measurable business impact.

🎯 Primary Focus

To design, deploy, and scale predictive and prescriptive analytics solutions while building the supporting data science capability, infrastructure, and governance required to embed AI‑powered decision‑making across the Merchant Division.

🔍 Key Responsibility Areas & Associated Tasks

🧠 1. Capability Build & Strategy

• Design and establish the data science capability from the ground up: standards, tooling, and ways of working
• Define the advanced analytics roadmap aligned to business priorities and unified customer view initiatives
• Evaluate, procure, and implement experimentation, MLOps, and model‑deployment infrastructure
• Ensure the capability is scalable, production‑ready, and business‑aligned

🤖 2. Modelling & Data Science Delivery

• Develop, validate, and deploy predictive and prescriptive models across use cases such as:
– Credit risk and affordability
– Fraud and financial crime
– Customer lifetime value and churn
– Personalisation and recommendation
• Apply a broad range of techniques including classical statistics, ensemble methods, deep learning, time‑series, and LLMs
• Build robust feature‑engineering pipelines across structured and unstructured datasets
• Lead A/B testing, experimentation, and causal‑impact analysis

⚙️ 3. Data & Engineering Collaboration

• Partner closely with Data Engineering to ensure modelling‑ready data platforms and feature stores
• Contribute to Golden Record / Master Data initiatives (identity resolution, entity matching)
• Champion data quality, lineage, and governance at the analytics layer
• Improve efficiency and reliability of end‑to‑end model deployment pipelines

🤝 4. Stakeholder Engagement & Leadership

• Translate complex analytical outputs into clear, actionable insights for executive and non‑technical audiences
• Act as a trusted analytics partner to Product, Risk, Compliance, Finance, and Operations
• Hire, mentor, and develop junior data scientists as the team scales
• Build a culture of scientific rigour, experimentation, and continuous learning

💡 Key Competencies Required

• Strategic insight with strong analytical judgement
• Commercial acumen and business‑outcome focus
• Advanced structuring and problem‑framing capability
• Adaptability and innovation mindset
• Persuasive communication and stakeholder influence
• Results orientation and delivery accountability

🎓 Experience & Qualifications

Minimum Experience

• 4+ years of end‑to‑end data science experience, including production deployment
• Demonstrated experience delivering AI and ML solutions beyond prototyping
• Strong Python proficiency across the modern data science stack, including:
– Modelling: scikit‑learn, XGBoost / LightGBM, PyTorch or TensorFlow
– LLM‑based solutions from POC to production (with safeguards)
– Data manipulation: pandas, Polars or equivalent
– Orchestration: Airflow, Prefect, or similar
– Experiment tracking: MLflow, Weights & Biases, or equivalent
• Strong SQL skills and experience with large‑scale data warehouses (Snowflake, BigQuery, Databricks)
• Experience in experimentation design and causal inference
• Proven ability to influence decisions through insight communication

Advantageous Experience

• Fintech, banking, insurance, or financial‑services experience
• Credit risk, fraud detection, or financial crime analytics
• Entity resolution, graph analytics, or MDM exposure
• dbt or modern transformation‑layer experience
• Experience building or scaling data science teams
• Familiarity with model‑risk‑management frameworks (e.g. SR 11‑7)
• Reinforcement learning or bandit optimisation methods

Qualifications & Certifications

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or Econometrics
• Post‑graduate qualification advantageous
• Data Science / Machine Learning certifications
• Cloud ML certifications (AWS, Azure, GCP)

🌟 Our Values

At Lesaka Merchant, we are guided by four core values:
✔ Entrepreneurial Spirit – We innovate boldly and act with ownership
✔ Integrity – We operate with honesty, trust, and transparency
✔ Collective Wisdom – We collaborate and leverage shared expertise
✔ Bias to Action – We deliver with urgency, discipline, and focus

📌 Preference will be made to support EE / AA measures.

🔥 Ready to Build and Lead Advanced Analytics at Scale?

If you are a hands‑on data science leader who thrives at the intersection of AI, analytics, and real‑world business impact, this role offers a rare opportunity to shape how data creates competitive advantage at Lesaka.

📩 Apply now — or share this opportunity with an exceptional Lead Data Scientist!

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