Jobs at Badger Holdings (Pty) Ltd

Key Responsibilities

Agency Leadership & Commercial Ownership

• Lead Honeyguide as a standalone business unit with full P&L accountability, including budgeting, cost management, and financial performance
• Design and implement a scalable agency operating model (services, pricing, SLAs, workflows, and resourcing)
• Drive efficiency, utilisation, and margin improvement
• Position Honeyguide as a trusted, high-value partner to internal stakeholders

Growth Strategy & Value Creation

• Develop and execute a growth strategy aligned to group commercial priorities
• Identify opportunities to scale services across brands and reduce duplication
• Partner with executive leadership to ensure marketing contributes to revenue growth and customer value
• Continuously evolve the agency’s offering in line with market trends and business needs

Client (Brand) Performance & Stakeholder Management

• Own performance and satisfaction across all brands serviced by Honeyguide
• Implement clear engagement models, feedback loops, and service standards
• Ensure marketing drives measurable outcomes across brand health, acquisition, retention, and CX
• Act as a senior escalation point, building strong stakeholder relationships

Marketing & Creative Excellence

• Ensure delivery of high-quality, insight-led, commercially effective marketing
• Set standards for creative excellence, brand consistency, and integrated campaigns
• Guide senior marketing leaders in translating strategy into impactful execution
• Balance strategic oversight with empowered delivery teams

Digital, Data & AI Enablement

• Integrate data, automation, and AI into agency operations and outputs
• Build capabilities for measurement, attribution, and performance optimisation
• Enable real-time insights and predictive decision-making
• Align technology investments with commercial outcomes and efficiency gains

Capability Building & Culture

• Build and lead a high-performing leadership team
• Define structures, roles, and career pathways to support scale
• Foster a culture of accountability, creativity, and continuous improvement
• Attract, develop, and retain top marketing and agency talent

Governance & Operational Excellence

• Establish robust processes, reporting frameworks, and performance dashboards
• Ensure compliance with data governance, brand standards, and regulations
• Implement best practices in agency operations and delivery management

Measures of Success

• A financially sound, scalable agency with clear P&L performance
• High stakeholder satisfaction across all serviced brands
• Demonstrable impact of marketing on revenue, acquisition, and retention
• Improved efficiency, utilisation, and cost-to-output ratios
• Strong adoption of digital, data, and AI capabilities
• A future-ready, high-performing team with strong leadership depth
• Enhanced brand positioning and market impact across the portfolio

Skills, Experience & Qualifications

Minimum Requirements:

• Bachelor’s degree in Business, Marketing, Commerce, or related field
• Extensive senior leadership experience within a marketing agency or agency-style environment (internal or external)
• Proven track record with P&L ownership and commercial accountability
• Experience building or scaling teams, operating models, and structures in complex organisations
• Strong background in data-driven marketing, digital channels, and performance marketing
• Demonstrated ability to work cross-functionally with commercial, product, technology, and data teams

Advantageous:

• Postgraduate qualification
• Experience leading transformation or building internal agencies

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What You'll Do

As our Data Business Analyst, you'll bridge the gap between business and technology by:

• Facilitating workshops to understand business challenges, opportunities and reporting needs.
• Gathering, analysing and documenting business requirements, business rules and functional specifications.
• Defining enterprise KPIs, metrics and business logic for implementation within modern data platforms.
• Working closely with Analytics Engineers to ensure business requirements are accurately translated into data models.
• Analysing data to identify trends, risks, opportunities and operational improvements.
• Building and contributing to dashboards, reports and analytical solutions that support business decision-making.
• Validating data quality, business logic and reporting outputs.
• Maintaining consistent business definitions, data standards and governance practices.
• Presenting insights and recommendations that influence strategic and operational decisions.
• Identifying opportunities to improve business performance through automation, AI and data-driven decision making.

Requirements

What You'll Bring

You'll be successful in this role if you have:

• At least 5 years' experience as a Business Analyst within a data, analytics, systems or technology environment.
• Strong stakeholder management and workshop facilitation skills.
• Experience defining business rules, KPIs and reporting requirements.
• Strong SQL skills for data investigation and validation.
• Experience working with Business Intelligence tools such as Qlik, Power BI or Looker.
• Excellent analytical thinking, problem-solving and communication skills.
• Experience working within Agile delivery environments.
• Knowledge of data governance principles and regulatory requirements.
• Confidence using AI tools to improve productivity and decision-making.

Advantageous Experience

• Experience with dbt or semantic layer concepts.
• Snowflake or other cloud data platforms.
• Python for data analysis.
• Git or version control tools.
• Insurance or financial services experience.
• Exposure to AI-enabled analytics or automation initiatives.

Qualifications

• Bachelor's degree in Business Analytics, Information Systems, Computer Science, Data Science, Statistics, Commerce or a related field.
• A recognised Business Analysis certification (IIBA CBAP/CCBA, BCS Business Analysis or equivalent) would be advantageous.
• Microsoft Power BI Data Analyst Associate, SQL certification or other relevant analytics certifications would be beneficial.
• Agile or Scrum certification would be advantageous.

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Key Responsibilities

Data Engineering

• Design and build scalable feature pipelines and training datasets for machine learning models.
• Develop and maintain high-quality data assets within Snowflake.
• Build reliable, monitored and well-documented data pipelines for model training and inference.
• Collaborate with Data Engineering teams to align with platform standards and architecture.
• Validate data quality and ensure consistency with business definitions.
• Apply data governance principles and regulatory requirements including POPIA, FAIS and TCF.

Machine Learning Operations (MLOps)

• Partner with Data Scientists to productionise machine learning models.
• Build and maintain deployment pipelines and model serving infrastructure.
• Implement CI/CD processes for machine learning workflows.
• Manage model versioning, experiment tracking and reproducible deployments.
• Monitor models for performance, reliability and data drift.
• Maintain documentation, auditability and model lineage.
• Support responsible AI practices, including explainability and model governance.
• Troubleshoot production issues and continuously improve model performance.

Engineering & Collaboration

• Help establish ML Engineering standards and best practices.
• Contribute to the architecture of our AI ecosystem across Azure and GCP.
• Work closely with Analytics Engineers to integrate machine learning into business solutions.
• Identify opportunities to improve automation, tooling and delivery.
• Proactively identify risks and recommend practical solutions.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Technology, Mathematics, Statistics or a related quantitative field.
• A postgraduate qualification in Artificial Intelligence, Machine Learning or Data Science will be advantageous.
• Relevant industry certifications in Azure, Google Cloud, Snowflake or Machine Learning are advantageous.

Skills & Experience

Essential

• 5+ years' experience in Machine Learning Engineering, Data Engineering or a similar role.
• Proven experience deploying machine learning models into production.
• Strong Python development skills.
• Advanced SQL skills.
• Experience with Snowflake or another cloud data warehouse.
• Experience with Azure cloud services.
• Knowledge of Git, CI/CD pipelines and modern software engineering practices.
• Experience with Docker and containerisation.
• Experience building feature engineering pipelines.
• Understanding of model monitoring, observability and drift detection.
• Knowledge of data governance and regulatory frameworks such as POPIA and FAIS.

Advantageous

• Experience with dbt.
• Databricks experience.
• Feature Store implementation and management.
• API development and model serving.
• Experience within insurance or financial services.
• Exposure to GCP environments.

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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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What You’ll Be Doing

• Build and maintain strong relationships with motor dealerships
• Act as the primary point of contact for your dealer portfolio
• Drive sales through consistent engagement (calls, follow-ups, and support)
• Identify opportunities to grow and strengthen accounts
• Resolve queries efficiently and ensure a high level of partner satisfaction
• Keep accurate records and actively manage your pipeline

Requirements

What We’re Looking For

• Matric (essential)
• Strong communication and relationship-building skills
• A proactive, results-driven mindset
• Ability to manage multiple accounts and priorities effectively
• Resilience and a strong sense of ownership
• Previous experience in sales, account management, or customer service (motor industry advantageous)
• Comfortable using CRM systems and Microsoft Office