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Senior Data Scientist - CPT

Senior Data Scientist - CPT

BETSoftwareCape Town, ZA
30+ days ago
Job description

Job title : Senior Data Scientist - CPT

Job Location : Western Cape, Cape Town

Deadline : February 26, 2026

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Job Description

We Want You :

  • Join BET Software in Cape Town as a Senior Data Scientist to lead advanced analytics and model development that directly supports key business decisions.
  • You’ll work with large-scale, complex datasets to uncover insights, design predictive models, and deliver solutions that solve real-world challenges.
  • This role requires proven expertise in machine learning, statistical analysis, and data science, along with the ability to collaborate across product, engineering, and business Teams.
  • You’ll also mentor junior Team members, champion best practices, and stay ahead of emerging AI trends.
  • Ready to deliver impact at a senior level?
  • Apply now.
  • You Bring :

  • At least 3–5 years’ experience across the data science workflow will be advantageous.
  • At least 3–5 years of proven experience as a Data Scientist, with expertise in machine learning, statistical analysis, and data visualisation, will be advantageous.
  • Strong understanding of data modelling, feature engineering, and model evaluation techniques.
  • Strong problem-solving and critical thinking skills, with the ability to work in cross-functional teams to deliver results.
  • Experience managing data-driven projects that drive business value.
  • Good written and verbal communication skills.
  • Strong attention to detail.
  • What You’ll Do :

    Job Responsibilities :

    Data Analysis and Modelling :

  • Apply statistical and machine learning techniques to analyse data and translate complex data sets to identify patterns, trends and actionable insights that drive business strategy and operational efficiency.
  • Develop predictive models, recommendation systems and optimisation algorithms to solve business challenges and enhance operational efficiency.
  • Transform raw data into meaningful features that improve model performance and translate business challenges into analytical problems, providing data-driven solutions.
  • Gather, clean, analyse and interpret data to develop predictive models and support data-driven decision-making.
  • Design experiments and statistical tests to validate hypotheses and measure the impact of implemented solutions.
  • Machine Learning and AI Development :

  • Build and implement advanced statistical and machine learning models to solve complex problems.
  • Identify data quality issues and collaborate with data engineers to resolve them.
  • Stay up to date with the latest advancements in AI and machine learning, implementing best practices.
  • Research, test and evaluate AI technologies to ensure the best tools and platforms are used to achieve business objectives.
  • Develop, implement and maintain scalable machine learning models for various applications.
  • Design and Planning of Fit-for-Purpose Solutions and Algorithms :
  • Design and implement testing frameworks to measure the impact of business interventions.
  • Utilise optimisation algorithms to improve business processes and efficiency.
  • Ensure designs meet best practices and are test, DevOps and support friendly.
  • Formulate supporting plans and communicate with stakeholders regarding dependencies and impact.
  • Actively contribute to design and planning meetings, discussions and documentation.
  • Collaborate with stakeholders to define success metrics and continuously refine solutions based on feedback and performance.
  • Collaboration and Stakeholder Engagement :

  • Collaborate with software engineers to integrate AI capabilities into company products, understand the data architecture, and ensure seamless data access, quality, and transformation pipelines.
  • Work closely with business leaders to understand their needs and deliver tailored data solutions.
  • Lead collaborative brainstorming sessions to identify innovative ways to apply data science across various business domains.
  • Technical Development and Innovation :

  • Stay current with technological advancements in data science, machine learning, and AI.
  • Continuously evaluate and experiment with new tools, libraries, and platforms to ensure the team uses the most effective technologies.
  • Lead end-to-end data science projects that support strategic goals, including requirements gathering, technical deliverable planning, quality assurance, and stakeholder management.
  • Conduct ongoing research to develop and implement new ideas, improved methods, systems, and work processes that result in higher quality and better outcomes.
  • Coaching and Mentoring :

  • Provide guidance, training and mentorship to team members, fostering a culture of learning and innovation.
  • Contribute to team development by designing and delivering end-user training and creating training materials.
  • Serve as a source of inspiration and a role model, demonstrating how to approach challenges with a problem-solving mindset.
  • Behavioural Outputs :

    Adaptability and Resilience :

  • Demonstrate flexibility and openness to change by adapting to evolving business needs and priorities.
  • Maintain a positive attitude and proactive mindset when facing change, embracing new technologies and methodologies with a growth mindset.
  • Collaborate effectively with diverse teams while maintaining a constructive attitude in dynamic and fast-changing environments.
  • Decision Making Quality :

  • Make confident, timely and fact-based decisions by drawing on a wide range of resources and collaborating with others.
  • Involve the team in decision-making processes to ensure transparency and alignment with project goals.
  • Consider both short-term and long-term impacts when making decisions, supporting the sustainability of the team and organisation.
  • Base decisions and evaluations on a careful and systematic review of relevant facts and information.
  • Be able to logically defend and explain judgements and decisions.
  • Ensure others fully understand the decision before proceeding.
  • Resourceful and Improving :

  • Find innovative ways to overcome challenges by following processes and effectively leveraging available tools, data and methodologies.
  • Continuously seek out new techniques, best practices and emerging trends in data science, AI and machine learning.
  • Generate new ideas, challenge the status quo, take calculated risks, support change and encourage innovation.
  • Actively contribute to team learning by sharing insights, tools and approaches that enhance overall performance.
  • Living our Spirit :

    Encourage open communication and collaboration among team members.

  • Foster an inclusive environment where diverse perspectives are respected and valued.
  • Recognise and celebrate individual and team achievements.
  • Promote a culture of innovation and experimentation.
  • Emphasise the importance of continuous learning and personal growth.
  • Support exploration of new technologies, tools and methodologies.
  • View challenges as opportunities for growth and learning.
  • Create a space where team members feel empowered to share ideas and opinions.
  • Promote a “raise your hand” mentality, where team members feel comfortable seeking help, offering insights or suggesting improvements.
  • Lead by example, demonstrating authenticity and integrity in all interactions.
  • Create a safe environment for honest feedback and constructive criticism.
  • Value authenticity over conformity, encouraging individuals to express their true selves.
  • Provide opportunities for skills development, training and career advancement.
  • Offer mentorship and guidance to support the career aspirations of team members.
  • Closing Date : 31 July 2025

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