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  • Posted: Dec 1, 2025
    Deadline: Not specified
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  • We bring an Out of the Ordinary approach to creating and managing wealth. Founded in South Africa as a small finance company, today we offer clients our services as a global bank and asset management group. Follow us on LinkedIn for unique insights from leading minds within the world of finance and Out of the Ordinary stories about our people, communit...
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    Content Performance & Distribution Manager- IWI

    Description

    • The W&I International Private Client team is looking for an experienced Content Performance and Distribution Manager to ensure our content reaches the right audiences, in the right places, and in formats that drive impact. This role connects content creators, brand managers, designers, paid media teams, and SEO partners—turning articles, videos, thought leadership pieces, and brand assets into high-performing content across social and paid channels.
    • The successful candidate will manage the full amplification process, from channel planning to quality control, ensuring every asset is optimised and adapted for maximum performance. The role demands strong judgement across organic social platforms, fluency in paid media principles, and the ability to translate complex topics into compelling, platform-fit content. Creative sensibility and the ability to craft concise, engaging social copy that reflects W&I International's brand tone are essential.
    • This is a strategic, operational hybrid role—not a hands-on paid media buying or content creation position. It is the role that ensures the effectiveness of the entire content ecosystem, making sure every piece is optimised, amplified, and performing where it matters most.

    Responsibilities

    Content Distribution and Amplification

    • Plan and manage the distribution strategy for new and existing content across paid and organic channels.
    • Adapt long-form content into social-ready formats, including short captions, carousels, cut-downs, subtitles, and platform-native hooks.
    • Identify opportunities to repurpose existing assets to extend content longevity and improve ROI.
    • Own channel-level formatting guidance for authors, creatives, and internal stakeholders.
    • Ensure every piece of content has a clear distribution plan before publishing.

    Paid Media Oversight

    • Ensure campaigns use the right content, in the right formats, with the right creative variations for each audience and platform.
    • Review media plans, creative specifications, targeting logic, and placement decisions with a critical and strategic eye.
    • Monitor campaign performance and guide optimisation priorities.
    • Maintain an up-to-date understanding of paid social and paid media best practices, ad formats, and platform changes.

    Organic Social Leadership

    • Own the content calendar for W&I International's social platforms, ensuring a balanced mix of thought leadership, brand storytelling, product-relevant content, and community engagement.
    • Translate authored content into engaging, platform-native social posts.
    • Collaborate with content writers, brand managers, and creative agencies to brief, refine, and polish assets.
    • Maintain high editorial and design standards across all organic content.

    Creative Direction and Design Execution

    • Create or refine design assets such as carousels, story frames, cut-downs, reels layouts, and static posts when required.
    • Quality-check all externally or agency-created assets to ensure visual consistency and brand adherence.
    • Collaborate closely with designers on complex assets to ensure they meet platform requirements and distribution needs.

    Workflow and Operations

    • Manage the content distribution pipeline end-to-end, ensuring timelines are clear and stakeholders remain aligned.
    • Maintain version control, manage approvals, and ensure both campaign and BAU content are delivered on time.
    • Implement repeatable content distribution processes and frameworks.
    • Ensure all assets have proper UTM tracking, metadata, and are correctly tagged and stored.

    Performance and Reporting

    • Partner with analytics teams and agencies to understand performance drivers and feed insights back into content creation and distribution planning.
    • Track and analyse the performance of organic and paid content, identifying patterns and optimisation opportunities.
    • Build a feedback loop that enables smarter, insight-led content development upstream.

    Qualifications, Experience and Skills

    • 5+ years in content distribution and social media management, including paid social or multi-channel media (agency or client side).
    • Ability to adapt content for platform-native formats across LinkedIn, Instagram, YouTube, X, and Meta.
    • Strong design skills using Adobe Creative Suite or Figma, with an understanding of brand systems.
    • Proven experience interpreting performance data and applying insights to improve paid and organic content.
    • Skilled in audience segmentation, creative best practices, and content performance drivers.
    • Strategic thinker with strong creative judgment and operational discipline to manage multiple projects.
    • Collaborative approach with internal teams and external agencies; confident in guiding partners.
    • Excellent communication, analytical mindset, and high attention to quality.
    • Proactive, adaptable, and commercially aware, with the ability to balance creativity and execution under pressure.

    go to method of application »

    Data Scientist

    Role Overview

    • The primary expectation of this role is to solve business problems through the extraction, analysis and interpretation of data using algorithmic, statistical and machine learning tools, in order to develop models that understand patterns and predict useful business outcomes (eg. Product and next best action recommendation, behavioural and lifestyle clustering, client lifetime value, etc). Combining this with data storytelling and effective communication skills, the ask is to quantify business value and support decision making by delivering a data story to the business in a meaningful and understandable way.
    • Our operating model is built around agency and autonomy, asking our team members to build end-to-end partnerships and drive solutions to completion as per the business need. From engaging stakeholders on the business requirement, to collaborating on project prioritisation, to developing the technical insights and solutions, to presenting the findings through data storytelling; you will own and drive projects while working with relevant internal and external team members.  Coupled with generating innovative ideas for new models, a risk-conscious approach to toolset and dataset selection as well as overall solution design is critical, along with a firm view to ensure fairness and minimise bias in model outputs.
    • Adherence to important regulatory standards such as POPIA is a must.

    Key Responsibilities

    • Gather data from structured and unstructured sources, whether internal or external, and clean and preprocess data to ensure quality and consistency
    • Utilise machine learning algorithms to design, develop, test, and review predictive and prescriptive models that align with and support our business objectives, using both on-premise and cloud-based infrastructure
    • Analyse and interpret data, trends and patterns and deliver insights, data stories and recommendations to enhance business strategy, both independently and collaboratively
    • In addition to model accuracy and selecting fit-for-purpose tools, ensure that bias mitigation and ethical considerations are cornerstones of model development
    • Develop graphs, dashboards, and presentations of project results and present to key stakeholders
    • Collaborate with ML Ops engineers to prepare models for productionisation in the cloud
    • Use feedback loops and general analysis to improve model performance over time
    • Offer specialised data science expertise and introduce new ML techniques where appropriate
    • Proactively manage projects for timely and accurate completion within scope of responsibility
    • Engage with key stakeholders to improve, deliver, pivot and review strategic initiatives
    • Develop new ML use cases and quantify their commercial viability
    • Engage in prioritisation discussions for projects to maximise commercial value and ensure alignment with strategic goals
    • Enhance model development processes to drive automation and reduce manual tasks
    • Evaluate current tools and technologies to develop use cases for upgrades and enhancements
    • Contribute to the broader data science community within Investec to share knowledge, collaborate in problem solving, drive tool usage, enhance processes, and forge new relationships
    • Mentor junior data scientists
    • Assist in enhancing data science literacy within the organisation
    • Collaborate to enhance our model governance frameworks and ensure these are applied to the building of advanced analytics solutions
    • Maintain the integrity of data processes to ensure continuous improvement of data quality that supports compliance with legal, regulatory and industry best practice
    • Comply with security and audit controls to protect data solutions and their environment
    • Keep abreast of latest developments in data science, data, technology, banking and global events

    Minimum Qualifications and Knowledge

    • A postgraduate degree in data science or a field related to data science, such as Computer Science, Statistics, Mathematics, Engineering, etc
    • 3-5 years of experience in development, testing, validation and monitoring of machine learning models
    • Evidence of experience with data-driven problem solving and statistical analysis (descriptive and inferential)
    • Experience with deploying ML models in production, including an understanding of ML Ops principles and best practices
    • Proficient in Python, SQL, and Jupyter notebooks (PySpark is beneficial)
    • Competent in visualisation tools (eg. PowerBI) and Microsoft Office (Excel, Powerpoint)
    • Preferable: Experience in DevOps practices, version control, etc
    • Preferable: Experience in cloud platforms and tools such as Microsoft Azure, including Azure ML, Azure Dev Ops (ADO), Azure ML Feature Store and Databricks

    Competencies

    • Ability to develop, test, and optimise machine learning models
    • Understanding of how models deliver business value required to advance strategy
    • Strong analytical and critical thinking skills
    • Ability to collaborate effectively with cross-functional teams
    • Excellent verbal and written communication skills
    • Inquisitive mindset
    • Ability to connect solutions to their commercial impact
    • A focus on ethical considerations in data science (bias, fairness, etc)
    • Comfort in iterative delivery
    • Results orientated, producing a high standard of work
    • Ability to work under time pressures on multiple projects
    • Attention to detail
    • Self-starter – must be proactive and productive with minimal direction
    • Ability to work in a fast-paced, technical, cross-functional environment

    Method of Application

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