Senior Data Scientist - CPT
BETSoftware
Date: 1 day ago
City: Cape Town, Western Cape
Contract type: Full time

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
Job Responsibilities:
Data Analysis And Modelling
Adaptability and Resilience:
At BET Software, we don't just recruit talent, we cultivate it. Our learning and development programmes, our various opportunities for growth, and our well-deserved incentives are what keep our All-Star Team the best amongst the rest.
Please note that only candidates who meet the stipulated minimum requirements will be considered.
If you have not been contacted within 30 days, kindly consider your application to be unsuccessful.
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.
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.
- 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 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.
- 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.
- 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.
- 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.
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.
- 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.
- 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.
- 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.
At BET Software, we don't just recruit talent, we cultivate it. Our learning and development programmes, our various opportunities for growth, and our well-deserved incentives are what keep our All-Star Team the best amongst the rest.
Please note that only candidates who meet the stipulated minimum requirements will be considered.
If you have not been contacted within 30 days, kindly consider your application to be unsuccessful.
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