Senior Data Scientist - CPT at BETSoftware

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