Jobs at Badger Holdings (Pty) Ltd

What You’ll Do

Lead & Inspire

• Manage, mentor, and grow a team of Data Scientists into a powerhouse of delivery.
• Build a culture where experimentation, collaboration, and results thrive.

Design & Deliver

• Oversee the creation, testing, and deployment of machine learning models that solve real business problems.
• Measure, quantify, and communicate the commercial impact of analytics solutions.
• Keep models relevant, accurate, and laser-focused on business goals.

Bridge Tech & Business

• Be the go-to liaison between data science and decision-makers.
• Translate complex analytics into plain, actionable English
• Ensure operational teams adopt and use model outputs effectively.

Drive Excellence

• Gather, refine, and document requirements for analytics projects.
• Push for best practices, smarter modelling approaches, and continuous process improvement.

Requirements

What You’ll Need to Bring

Essential:

• Degree or Honours in Actuarial Science.
• 7+ years’ experience in insurance or financial services (short-term insurance? Even better).
• Proven track record in building statistical/machine learning models.
• Skill in turning model outputs into business gold.
• Leadership experience in Data Science, Analytics, or Actuarial teams.
• Experience with claims modelling & survival analysis in insurance.
• BI tool mastery (Power BI, Qlik Sense, Tableau, etc.).
• Exceptional stakeholder engagement and communication skills.

Preferred:

• Hands-on skills in Python, R, SQL, and cloud platforms like Snowflake.
• Experience shaping both technical and business requirements.
• Strong grasp of data-driven decision frameworks.

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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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Your day-to-day will include:

• Preparing and transforming data for machine learning (cleaning, feature engineering, optimisation)
• Conducting exploratory analysis to uncover trends and guide model design
• Building, testing, and deploying machine learning models aligned to business needs
• Collaborating with actuarial teams to align assumptions and modelling approaches
• Validating models and ensuring performance, accuracy, and reliability
• Monitoring live models for drift and performance degradation
• Maintaining, retraining, and improving models over time
• Creating clear documentation for models, pipelines, and processes
• Developing dashboards and reporting tools to track performance and KPIs
• Communicating insights and recommendations to both technical and non-technical stakeholders

About you

You’re someone who enjoys solving real problems and not just building models for the sake of it. You’re curious about the “why” behind the data and motivated by the impact your work can have.

Requirements

Requirements:

• A degree (Honours preferred) in Data Science, Actuarial Science, Statistics, Mathematics, or a related field
• 3+ years’ experience in data science or machine learning roles
• Strong Python and R skills, with proven experience building and deploying models
• Solid experience across the full ML lifecycle (data → model → deployment)
• Hands-on experience with statistical modelling, machine learning, and time series forecasting
• The ability to translate technical outputs into clear business value
• Strong communication and stakeholder engagement skills, particularly with actuarial teams
• A proactive, energetic mindset and a genuine passion for data and innovation

Nice to have:

• Experience in insurance (especially short-term insurance)
• Exposure to CLTV modelling, claims modelling, survival analysis, or actuarial-related work
• Experience with dbt, Snowflake, GCP, or similar cloud platforms
• Familiarity with MLOps practices and machine learning platforms
• Experience with BI tools (Power BI, Tableau, Looker, Qlik, etc.)

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What you will be doing:  

• You’ll lead the delivery of strategic technology projects from planning through implementation, ensuring teams stay aligned, focused and accountable.
• Working across architecture, software development, QA, operations and business teams, you’ll remove roadblocks, manage risks, balance competing priorities and keep delivery on track.
• You’ll also help establish delivery best practices, improve governance and reporting, and create an environment where high-performing teams can consistently deliver quality software.
• This role is instrumental in supporting Softsure’s Clean Architecture transformation and driving continuous improvement across our technology landscape.

Requirements

About you

You’re an experienced Project Manager with a strong background delivering software development projects, not construction, infrastructure or general business projects.

You’ll bring:

• A Bachelor’s Degree in Project Management, Information Systems, Computer Science, Business Management or a related field
•  At least 8 years’ experience managing software development or technology projects.
• Proven experience delivering complex, cross-functional software initiatives.
• Strong Agile project delivery experience.
•  Experience working closely with software developers, solution architects, QA teams and business stakeholders. 
• Solid knowledge of Azure DevOps, GitHub or similar delivery management platforms.
• Experience presenting project status, risks and delivery updates to senior leadership.
• Professional certifications such as PMP, PRINCE2, Scrum Master or AgilePM will be advantageous, as will experience within insurance or technology transformation programmes.
• Most importantly, you’re someone who leads from the front. You’re organised, decisive, commercially aware and comfortable navigating complex technical environments. You ask the right questions, build credibility quickly and know how to turn strategy into successful delivery.

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About the role

• At Dotsure, learning isn't just about training people, it's about helping our teams grow, adapt, and thrive in a fast-changing world.
• As our Content Technician, you'll take learning concepts, source material, and subject matter expertise and transform them into engaging, impactful learning experiences that people want to complete. From e-learning modules and microlearning content to videos, guides, assessments, and multimedia resources, you'll bring learning to life through creativity, technology, and strong instructional design.
• You'll work closely with our Learning & Development team and business stakeholders to create learning solutions that support performance, build capability, and improve the employee experience. You'll also play an important role in our digital transformation journey by exploring and applying AI-powered tools that improve how we create, deliver, and experience learning.

Requirements

About you

• You're a creative thinker with a passion for learning, technology, and innovation.
• You enjoy taking complex information and turning it into something clear, engaging, and easy to understand. You're naturally curious about emerging technologies, particularly AI, and you're excited by opportunities to use them to work smarter and create better learning experiences.

Requirements:

• Diploma or Degree in Learning & Development, Education, Instructional Design, Multimedia Design, HR, Communications, or a related field.
• Equivalent practical experience in learning content development, instructional design, content creation, or a similar field will be considered (no less than 2 years)
• Strong content writing, editing, and proofreading skills
• Experience creating learning materials for adult learners
• Confidence using digital content creation tools and multimedia platforms
• A solid understanding of instructional design principles
• An interest in AI tools such as ChatGPT, Claude, Gemini, or Copilot
• Strong collaboration skills and the ability to work with subject matter experts and stakeholders
• Excellent attention to detail and project coordination abilities