Data Science Lead | George, Western Cape | On-site

Badger Holdings

Location
George, Western Cape
Minimum qualification
Bachelor's degree
Closing date

First listed . Last checked at source .

In brief

**Job Title:** Data Science Lead **Company:** Badger Holdings --- **Overview** This role is for a Data Science Lead at Badger Holdings, based on-site in George, Western Cape. The successful candidate will lead a team of three Data Scientists and one Machine Learning Engineer, driving strategic AI initiatives across the business. **What you will do** * Lead the end-to-end delivery of machine learning and AI projects from business discovery through deployment and monitoring. * Build, validate and deploy predictive models across customer lifetime value CLV, fraud detection, lapse prediction, pricing optimisation, claims prediction and customer segmentation. * Work closely with stakeholders across underwriting, claims, finance and operations to identify high-value opportunities. * Translate commercial challenges into scalable data science solutions. * Ensure models are production-ready, explainable, governed and deliver measurable business value. * Present insights and recommendations to senior leadership and executive stakeholders. * Mentor, coach and develop the Data Science team while establishing technical best practices. * Collaborate with Data Engineering, Analytics Engineering and ML Engineering to deliver robust AI solutions. * Contribute to ARC's evolving AI ecosystem across Azure, GCP and modern cloud data platforms. **Requirements (from the original advert)** * **Qualifications:** * Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative discipline. * A postgraduate qualification in a relevant field is advantageous. * Relevant cloud, AI or machine learning certifications (Azure, Google Cloud, AWS, Databricks or Snowflake) will be advantageous. * **Essential experience:** * 5+ years' experience in Data Science, Machine Learning or Artificial Intelligence. * Previous experience leading or mentoring Data Science teams. * Proven success delivering production machine learning models with measurable business impact. * Strong Python and SQL skills. * Experience across supervised, unsupervised and time-series modelling techniques. * Experience owning the full machine learning lifecycle from problem definition to production deployment. * Strong stakeholder engagement and business partnering skills. * Experience presenting technical concepts to senior leadership and non-technical audiences. * Knowledge of cloud platforms such as Azure, AWS or Google Cloud Platform (GCP). * Understanding of model governance, explainability and responsible AI. * **Highly advantageous:** * Insurance or Financial Services experience. * Experience with fraud detection, customer propensity, churn or CLV modelling. * MLOps and production deployment pipelines. * Snowflake, dbt or modern cloud data platforms. * Azure ML, Vertex AI, BigQuery ML or Databricks. * Exposure to Generative AI, Large Language Models (LLMs) or AI Agent frameworks. * Experience working within regulated environments (POPIA, FAIS, TCF). **Who should apply** This role is suitable for candidates who combine technical excellence with strong leadership and commercial thinking. **Deadline** Not specified **Reference** Original posting: https://www.myjobmag.co.za/job/data-science-lead-george-western-cape-on-site-badger-holdings-pty-ltd-2 Source: myjobmag

Summary drafted with AI assistance from the original advert. The advert itself is the authority — how we use AI.

At a glance

  • At least 5 years of experience.
  • Python
  • SQL
  • AWS
  • Azure
  • Google Cloud

Extracted automatically from the advert; confirm requirements on the original listing.

Job description

What you'll do As our Data Science Lead, you'll lead a team of three Data Scientists and one Machine Learning Engineer while driving strategic AI initiatives across the business. You'll: * Lead the end-to-end delivery of machine learning and AI projects from business discovery through deployment and monitoring. * Build, validate and deploy predictive models across customer lifetime value CLV, fraud detection, lapse prediction, pricing optimisation, claims prediction and customer segmentation. * Work closely with stakeholders across underwriting, claims, finance and operations to identify high-value opportunities. * Translate commercial challenges into scalable data science solutions. * Ensure models are production-ready, explainable, governed and deliver measurable business value. * Present insights and recommendations to senior leadership and executive stakeholders. * Mentor, coach and develop the Data Science team while establishing technical best practices. * Collaborate with Data Engineering, Analytics Engineering and ML Engineering to deliver robust AI solutions. * Contribute to ARC's evolving AI ecosystem across Azure, GCP and modern cloud data platforms. What we're looking for * You'll thrive in this role if you combine technical excellence with strong leadership and commercial thinking. Requirements Qualifications * Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative discipline. * A postgraduate qualification in a relevant field is advantageous. * Relevant cloud, AI or machine learning certifications Azure, Google Cloud, AWS, Databricks or Snowflake will be advantageous. Essential experience * 5+ years' experience in Data Science, Machine Learning or Artificial Intelligence. * Previous experience leading or mentoring Data Science teams. * Proven success delivering production machine learning models with measurable business impact. * Strong Python and SQL skills. * Experience across supervised, unsupervised and time-series modelling techniques. * Experience owning the full machine learning lifecycle from problem definition to production deployment. * Strong stakeholder engagement and business partnering skills. * Experience presenting technical concepts to senior leadership and non-technical audiences. * Knowledge of cloud platforms such as Azure, AWS or Google Cloud Platform GCP. * Understanding of model governance, explainability and responsible AI. Highly advantageous * Insurance or Financial Services experience. * Experience with fraud detection, customer propensity, churn or CLV modelling. * MLOps and production deployment pipelines. * Snowflake, dbt or modern cloud data platforms. * Azure ML, Vertex AI, BigQuery ML or Databricks. * Exposure to Generative AI, Large Language Models LLMs or AI Agent frameworks. * Experience working within regulated environments POPIA, FAIS, TCF.

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