Jobs Available at Badger Holdings (Pty) Ltd

Key Responsibilities

You'll be responsible for:

• Designing creative assets for digital, print and marketing campaigns.
• Producing engaging content for social media, websites, email marketing, paid media and digital advertising.
• Creating print-ready artwork for brochures, posters, signage, promotional material and other marketing collateral.
• Maintaining brand consistency across all customer touchpoints.
• Collaborating with marketers, copywriters and other stakeholders to develop creative concepts.
• Presenting design ideas and incorporating feedback into final creative solutions.
• Managing multiple projects while meeting agreed deadlines.
• Ensuring all artwork is accurate, high quality and production ready.

Minimum Requirements

To be successful in this role, you'll have:

• A Diploma or National Diploma in Graphic Design, Visual Communication or a related field (or equivalent practical experience supported by an exceptional portfolio).
• At least 3 years' professional graphic design experience within an agency or in-house marketing environment.
• A portfolio demonstrating strong commercial design work across digital and print channels.
• Experience applying brand guidelines consistently across multiple platforms.
• The ability to manage multiple projects and competing deadlines.

Essential Technical Skills

You'll demonstrate proficiency in:

• Adobe Photoshop
• Adobe Illustrator
• Adobe InDesign
• Typography and layout design
• Colour theory and visual composition
• Digital content creation
• Print production and artwork preparation
• Working knowledge of Figma and Canva will be advantageous.

Preferred Experience

It would be beneficial if you also have experience in:

• Consumer-facing brands
• Integrated marketing campaigns
• Financial services or insurance
• Motion graphics or video editing
• AI-powered creative tools
• UX/UI design

What We're Looking For

We're looking for someone who demonstrates:

• Creativity and innovative thinking
• Strong attention to detail
• Excellent communication and collaboration skills
• Effective planning and time management
• Adaptability in a fast-paced environment
• Customer-focused thinking
• Accountability and ownership
• A passion for continuous learning and creative excellence

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What you'll be doing

• As our Creative Copywriter, you'll help bring the Dotsure brand to life across every customer touchpoint. Working alongside designers, marketers, strategists and digital specialists, you'll create impactful copy that connects with audiences and delivers real business results.

Requirements

You'll create content for a variety of channels, including:

• Integrated marketing campaigns
• Brand and product launches
• Website and landing pages
• Social media (organic and paid)
• Email marketing and CRM campaigns
• Google Ads and digital advertising
• Customer communications
• Video scripts and multimedia content
• Internal communications and employer branding
• Public relations and partnership campaigns
• You'll also contribute creative ideas during campaign planning, present concepts confidently and ensure every piece of communication reflects the unique Dotsure brand voice.

What you'll bring

You'll be a naturally curious storyteller who enjoys solving problems with creativity and words.

We're looking for someone with:

• A Degree or Diploma in Copywriting, Journalism, Communications, Marketing, English or a related field (or equivalent practical experience supported by a strong portfolio)
• 3–5 years' experience as a Copywriter, Creative Copywriter or Content Writer
• A portfolio demonstrating strong campaign thinking and multi-channel copywriting
• Experience writing for digital marketing, social media and integrated campaigns
• Exceptional English writing, editing and proofreading skills
• Strong conceptual thinking and storytelling ability
• The ability to simplify complex topics into engaging, customer-friendly content
• Excellent collaboration and communication skills
• Strong organisational skills with the ability to manage multiple projects and deadlines
• Experience within financial services, insurance or an advertising agency will be advantageous but isn't essential.

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About the Role

• As our Machine Learning Engineer, you'll operate at the intersection of Data Engineering and Machine Learning Operations (MLOps), turning experimentation into production-ready AI solutions.
• Approximately 60% of your role will focus on building reliable data pipelines, feature datasets and Snowflake assets that power model development.
• The remaining 40% will focus on MLOps, including deploying, monitoring and maintaining machine learning models in production while establishing engineering best practices.

Requirements

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.

About You

You'll thrive in this role if you are:

• A collaborative engineer who enjoys partnering with Data Scientists.
• Passionate about building reliable, scalable machine learning solutions.
• Comfortable balancing data engineering with production ML engineering.
• Curious about emerging AI technologies and best practices.
• Pragmatic, solutions-focused and commercially aware.
• Someone who takes ownership and follows work through to completion.
• Committed to engineering quality, documentation and continuous improvement.

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About the Role

• ARC AI builds AI agents as products: systems that operate autonomously across business functions, handle real customer interactions, and deliver measurable outcomes in a regulated insurance environment. This is not an experimentation function. We ship.
• We are looking for a Senior Software Engineer who has built and operated AI agent systems in production. Someone who knows what it takes to move an agent from prototype to live deployment, and who understands that evaluation, not iteration speed, separates reliable AI products from expensive demos.

Requirements

What You Will Own

• You will design, build, and operate the AI agent systems that power ARC AI products. This means owning the full arc: architecture, evaluation pipelines, production reliability, guardrails, and the backend integrations that connect agents to real enterprise data.
• You will set the engineering standards the rest of the team follows. Evaluation is a first-class responsibility here, not a QA afterthought. Securing an agent means architecting enforcement outside the model; defences sit at the execution boundary, not inside the system prompt. Compliance with POPIA and GDPR is an architectural decision you make at the start, not a checkpoint at the end.
• The architectural decisions you make in this role will be the ones every subsequent engineer builds on.

What We Require

Non-negotiable

• Demonstrated experience building and shipping AI agent systems in production: not demos, not internal tools that never went live
• Ownership of an evaluation pipeline for a production AI system: you defined the metrics, built the framework, and used it to make deployment decisions
• Experience debugging production AI failures: you have traced a silent agent degradation to its root cause in a live system
• Proficiency in Python and LLM frameworks (LangChain, LlamaIndex, or equivalent)
• RAG architecture: retrieval pipeline design, vector database implementation, chunking and embedding strategy
• API design and backend integration at production scale
• Secure tool access patterns for agentic systems: you know where LLM reasoning ends and deterministic enforcement must begin, and you have built the boundary between them
• Experience implementing guardrails: input validation, output filtering, and execution-layer prompt injection defence
• CI/CD for agentic systems: you have implemented progressive delivery pipelines for agents, including instrumentation of tool invocations and decision points, staging with regression benchmarks, and canary deployment to detect behavioural drift before full rollout

 Strong Advantage

• Experience in regulated financial services, insurance, or healthcare environments
• Familiarity with graph-based agentic orchestration frameworks (LangGraph or equivalent), particularly durable execution and human-in-the-loop checkpointing in regulated environments
• Familiarity with Azure AI tooling and services
• MLOps practices: monitoring, observability, cost management for inference workloads
• CRM and enterprise system integration

Educational Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science, or a related field
• OR equivalent practical industry experience building and deploying production-grade AI systems

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About the role

• You’ll turn powerful AI systems into real, usable products; the kind customers and teams rely on every day. At ARC AI, we’re building intelligent agents that operate in a regulated insurance environment, and your role is to make them work in the real world.
• This means designing and building the interfaces, APIs, and product layer that sit between AI and people. You’ll shape how users interact with AI: from chat interfaces and workflows to human-in-the-loop review systems that keep humans in control of agent decisions before they reach customers. Ensuring everything works smoothly, even when the AI doesn’t.
• You’ll own the full stack: frontend experiences that handle streaming responses and unpredictable outputs, backend services that connect AI to core systems, and the pipelines that ship it all into production.
• You’ll also build the observability and feedback loops that help us continuously improve how these agents perform in production, not just in evaluation, but in the real product.
• This is a hands-on, high-ownership role where what you build is the product, seen and used by customers and leadership alike.

Requirements

About you

• You’re an experienced full-stack engineer who has already shipped AI-powered products into production.
• You understand that building for AI is different. You’ve worked with non-deterministic systems, handled variable latency, and designed experiences that gracefully manage failure, partial responses, and uncertainty.

You’re confident across the stack:

• Modern frontend frameworks (React or similar)
• Backend/API development (Node.js, Python, or similar)
• REST/GraphQL APIs at scale
• Secure, compliant data handling in regulated environments
• You’ve built systems where reliability, security, and control matter, including authentication, validation, and enforcing boundaries at the API layer (not relying on the model to behave).
• You’re also comfortable owning the full lifecycle: from design and development to CI/CD and deployment.
• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent practical experience demonstrating shipped production AI work
• 5+ years’ experience in full-stack software engineering roles
• Demonstrated experience shipping user-facing AI or LLM-powered products into production environments

Bonus points

We’d love to hear from you if you’ve also worked with:

• Conversational interfaces, Azure, or LLM observability tools
• Complex system integrations like CRM platforms
• Training or certifications in secure software development or data protection (e.g. GDPR/POPIA awareness)

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What you’ll be doing (and why it matters)

• You’ll play a key role in building the foundation that powers data across the business.
• Working closely with analysts, data scientists, and stakeholders, you’ll design and deliver data solutions that turn raw data into something trusted, usable, and impactful.
• A big part of your focus will be helping us move from legacy systems to a modern stack using Estuary, dbt, GCP, and Snowflake, not just executing the migration, but helping define how we do things going forward.

Requirements

Your day-to-day will include:

• Designing and building scalable ELT pipelines from multiple data sources
• Developing clean, well-structured data models using dbt
• Optimising data models and workloads within Snowflake
• Transforming raw data into high-quality, analytics-ready datasets
• Implementing data quality checks, monitoring, and observability
• Improving performance and managing cloud cost efficiency
• Applying engineering best practices (CI/CD, testing, code reviews)
• Collaborating with cross-functional teams to deliver practical, scalable solutions
• Contributing to standards, documentation, and mentoring junior engineers

What you bring

You’re someone who takes ownership, enjoys solving problems, and cares about doing things properly, not just quickly.

Requirements:

• 4–6+ years’ experience in Data Engineering or a similar role
• Strong SQL skills and experience working with complex transformations
• Proficiency in Python (or similar) for data processing and automation
• Experience building ELT pipelines in cloud environments (AWS, Azure, or GCP)
• Hands-on experience with modern data warehouses (e.g. Snowflake, Synapse)
• Familiarity with tools like dbt, Airflow, or Dagster
• Experience working with structured and semi-structured data (JSON, Parquet)
• A solid understanding of data governance, security, and best practices

Bonus if you’ve worked with:

• Real-time/streaming technologies (Kafka, Spark Streaming)
• BI tools like Qlik, Power BI, Looker, or Tableau
• Qlik Replicate / Compose or similar tools
• Agile delivery environments (Jira, Azure DevOps)
• Cloud certifications or exposure to DevOps practices

Why this role is worth your time

• You’ll help build (not inherit) a modern data platform
• You’ll work with a forward-looking tech stack (dbt, Snowflake, GCP)
• You’ll have real input into architecture, standards, and best practices
• You’ll be part of a growing data function where your impact is visible
• You’ll have the opportunity to mentor and shape how the team evolves

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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

What This Role Is Not

• Not a passive admin role, consistent engagement and follow-ups are required
• Not purely inbound, you will need to actively drive conversations and opportunities
• Not suited to someone who avoids targets or accountability
• Not a short-term stepping stone, this role requires commitment to building and growing a portfolio
• Not for someone who struggles with pace, pressure, or managing multiple priorities

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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.

The Kind of Person Who Will Thrive Here

You're someone who:

• Takes ownership and enjoys solving complex business problems.
• Is naturally curious and enjoys asking "why?"
• Thinks commercially and understands how data creates business value.
• Can translate technical concepts into language business stakeholders understand.
• Builds strong relationships across all levels of an organisation.
• Enjoys working in collaborative, fast-paced environments.
• Is passionate about analytics, emerging technologies and continuous learning.

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About the role

• You’ll be at the centre of our Data team’s projects, helping us move from ideas and plans to successful delivery.
• You’ll coordinate activities across projects, keep track of timelines and actions, and make it easier for technical and business teams to work together effectively.
• Your day-to-day could include:
• Coordinating project plans, timelines, milestones and deliverables.
• Tracking actions, dependencies and outstanding items to keep projects moving.
• Organising project meetings and making sure decisions and next steps are clearly captured.
• Following up with stakeholders and team members on commitments and deadlines.
• Maintaining project documentation, status updates and reporting.
• Identifying potential delays, risks or roadblocks and raising them early.
• Helping coordinate communication between the Data team and other areas of the business.
• Supporting project leads and team members with the practical details that make delivery happen.
• You won’t need to be a Data Engineer or technical specialist. You will, however, need to be comfortable working in a technical environment, learning the language and asking questions when something isn’t clear

Requirements

About you

• You’re the person who notices when something has fallen through the cracks and does something about it.
• You’re organised without being rigid, comfortable juggling different priorities and confident enough to follow up when you need an answer.

We’re looking for someone with:

• Experience in project coordination, project administration or a similar delivery-focused role.
• Strong organisational and time-management skills.
• The ability to manage multiple actions, deadlines and priorities at once.
• Clear, confident written and verbal communication.
• Strong attention to detail and a practical approach to problem-solving.
• Confidence working with different stakeholders and personalities.
• Experience using project management and collaboration tools.
• Good working knowledge of Microsoft Office or similar productivity tools.
• Exposure to Data, IT, technology or Agile environments would be an advantage.
• Most importantly, you take ownership. You don’t just record an action — you help make sure it happens.

Minimum requirements

• At least 3 years’ experience in project coordination, project administration, PMO support or a similar delivery-focused role.
• Demonstrated experience coordinating project plans, timelines, meetings, actions, dependencies and deliverables.
• Strong organisational and time-management skills, with the ability to manage multiple priorities simultaneously.
• A practical understanding of business processes and workflows, with the ability to document, coordinate and identify opportunities for improvement.
• Excellent written and verbal communication skills.
• Strong attention to detail and consistent follow-through on commitments.
• Confidence engaging with stakeholders across different teams and levels of seniority.
• Proficiency in Microsoft Office, particularly Excel, PowerPoint, Word and Teams.
• Experience using project management or collaboration tools such as Monday.com, Asana, Trello or similar.
• Proficiency in AI productivity tools such as Claude, ChatGPT and Microsoft Copilot, with the ability to use them responsibly to support planning, documentation, communication and delivery.
• Ability to identify potential delays, risks and roadblocks and escalate them promptly.
• Comfortable working in a technical environment and willing to learn data and technology terminology.
• A proactive, ownership-driven approach, you do not simply record actions; you help ensure they are completed.

Advantageous

• Diploma or degree in Project Management, Business Administration, Information Systems or a related field.
• Project management certification such as CAPM, PRINCE2 Foundation or an Agile qualification.
• Previous experience in a Data, IT, technology or Agile delivery environment.
• Experience supporting several concurrent projects or programmes.

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About the role

• You’ll work alongside the Data team to help turn raw information into reliable, useful data products.

Your work could include:

• Building and maintaining data pipelines and integrations.
• Working with databases, data models and transformation processes.
• Writing clean, efficient SQL and code.
• Helping improve data quality, reliability and performance.
• Supporting APIs and services that connect data to applications.
• Building or enhancing simple front-end interfaces, dashboards or internal tools that allow people to interact with data.
• Troubleshooting issues and finding practical ways to solve them.
• Working with the wider team to understand a need and help take a solution from data through to something a user can actually see and use.
• You won’t be expected to know everything from day one. What matters is that you have solid foundations, enjoy figuring things out and are keen to grow quickly.
• About you
• You’ll probably thrive here if you’re naturally curious, technically minded and enjoy building things.

Requirements

We’re looking for someone with:

• A relevant degree, diploma or equivalent practical experience in Computer Science, Data Science, Information Systems, Software Development, Engineering or a related field.
• Some experience with SQL and relational databases.
• Exposure to a programming language commonly used in data or software development, such as Python.
• An understanding of data structures, data transformation and basic data engineering concepts.
• Some exposure to front-end development using technologies such as JavaScript/TypeScript, HTML and CSS, ideally with a framework such as React, Angular or similar.
• Familiarity with APIs, Git/version control and modern development practices would be useful.
• An interest in cloud platforms, data warehouses and modern data tooling is a plus.
• Just as importantly, you’re someone who asks good questions, enjoys learning from others and doesn’t mind getting stuck into a problem you haven’t seen before.