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Data Science Team Manager - CPT

Data Science Team Manager - CPT

BETSoftwareCape Town, ZA
30+ days ago
Job description

Job title : Data Science Team Manager - CPT

Job Location : Western Cape, Cape Town

Deadline : February 26, 2026

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Job Description

We Want You :

  • Join our growing Team! We’re looking for a Data Science Team Manager based in the Cape Town to support the strategic goals of our organisation by leading the development and deployment of AI, machine learning, and big data projects.
  • In this role, you’ll guide a skilled Team, align technical initiatives with business objectives, manage day-to-day activities, and oversee resources, timelines, and stakeholder relationships.
  • You’ll be responsible for fostering innovation, implementing best practices, and ensuring the successful delivery of projects that make a measurable impact.
  • This role calls for a strong leader who can balance technical expertise with strategic oversight.
  • Lead your team to success, apply now!

    • You Bring :

  • At least 10 years in a technical role within the IT industry.
  • At least 3-5 years’ Proven experience in managing technical Teams.
  • Strong experience facilitating timely product / project delivery.
  • Detailed knowledge of the SLDC and management of software projects.
  • Result driven, despite changing requirements and environments.
  • Excellent written and verbal communication skills.
  • Strong attention to detail.

    • What You’ll Do : Job Responsibilities

    Strategy, Objectives, and Execution :

  • Collaborate with senior leadership to align data science, AI, and big data initiatives with the organisation’s broader strategic goals.
  • Develop and manage the execution of long-term technical roadmaps for AI and data science projects, ensuring scalability, performance, and sustainability.
  • Oversee the evaluation and adoption of new technologies, tools, and methodologies that enhance the team’s capabilities and meet business requirements.
  • Ensure that data science projects are optimised for performance, scalability, and security especially as data volumes grow.
  • Allocate resources efficiently, ensuring that human, technical, and financial assets are aligned with project priorities and timelines.
  • Drive the decision-making process around architecture, technologies, and methodologies to ensure solutions are cost-effective and deliver tangible value.

    • Knowledge Management :

  • Foster a culture of continuous learning and innovation by encouraging the exploration of new AI, machine learning techniques, and big data technologies.
  • Support and lead the team in adapting to new tools, technologies, and methodologies, ensuring effective change management practices are in place.
  • Maintain and enforce adherence to data science standards, documentation protocols, and best practices across all team projects.
  • Serve as an escalation point for technical challenges, assisting in resolving issues and ensuring solutions meet business requirements.
  • Promote the adoption of emerging technologies such as new multimodal machine learning models, advancements in big data storage and processing, and other innovations that benefit the organisation.

    • Stakeholder Management :

  • Build and maintain strong relationships with key stakeholders across the organisation, including senior leadership, product teams and business units.
  • Communicate team progress, key decisions and technical strategies to both technical and non-technical stakeholders, ensuring alignment with business objectives.
  • Act as the primary technical point of contact for non-technical teams, simplifying complex data science and AI concepts to support broader understanding.
  • Ensure that all project communications, including updates and escalations, are documented and shared efficiently with all relevant stakeholders.

    • Team Management :

  • Lead a team while ensuring effective collaboration and alignment with organisational goals.
  • Manage team performance by setting clear objectives, providing ongoing feedback and conducting regular performance reviews.
  • Ensure that the team follows best practices for data science, machine learning and big data tools, promoting a high standard of technical excellence.
  • Guide the team through the design, development and deployment of AI models and big data solutions that address business challenges.
  • Facilitate collaboration across cross-functional teams to ensure smooth project execution.
  • Manage day-to-day operations, ensuring timely delivery of data science projects and achievement of business objectives.

    • Behavioural Outputs :

    Talent Management :

  • Foster a culture of professional growth by ensuring team members have the skills and resources needed for both current and future projects.
  • Provide mentorship, coaching and opportunities for knowledge sharing within the team, helping to build a strong learning environment.
  • Promote a workplace culture based on respect, integrity and open communication, encouraging collaboration and innovative thinking.
  • Ensure a focus on succession planning and reducing key person dependency, supporting business continuity through talent development.
  • Lead talent acquisition efforts to recruit high-quality data science professionals and drive team excellence.

    • Adaptability and Resilience

  • Demonstrate flexibility and openness to change by adapting leadership style and strategies in response to shifting priorities, technologies or business goals.
  • Manage and thrive in high-pressure situations by adjusting plans as necessary to meet changing business demands.
  • Adapt communication and interpersonal approaches based on the needs and dynamics of different teams or stakeholders.
  • Maintain a positive attitude and proactive mindset in the face of change, ensuring the team stays motivated and aligned with organisational goals

    • Decision Making Quality

  • Make confident, well-informed decisions that balance technical feasibility, business objectives and resource constraints.
  • Involve the team in decision-making processes to ensure transparency and broad alignment with project goals.
  • Consider both short-term and long-term implications when making decisions, supporting the team’s and organisation’s sustainability.
  • Make data-driven decisions by relying on comprehensive analysis and collaboration with other departments to deliver effective solutions.
  • Communicate decisions clearly, making sure all stakeholders understand the rationale and expected outcomes.

    • Develops Talent

  • Collaboratively set performance goals with team members, ensuring clarity around expectations and objectives.
  • Provide structured and ongoing feedback to support both professional and personal growth.
  • Maintain a forward-looking skills matrix to give team members opportunities to learn and advance in their careers.
  • Foster an environment that encourages innovation, creative thinking and taking calculated risks.
  • Support the development of leadership skills by identifying potential leaders and offering meaningful growth opportunities.

    • Resourceful and Improving

  • Drive continuous improvement by challenging the status quo and exploring opportunities for innovation within data science workflows.
  • Encourage the team to share new ideas and experiment with different technologies to solve complex problems.
  • Proactively identify ways to optimise processes, enhance efficiency, and leverage new tools or methods to improve team performance.
  • Support a culture of experimentation and feedback, ensuring that lessons from both successes and setbacks are applied to future work.

    • Living the Spirit

  • Encourage open communication and collaboration among team members.
  • Foster an inclusive environment where diverse perspectives are acknowledged and valued.
  • Recognise and celebrate team achievements and success.
  • Promote a culture of innovation and experimentation within the team.
  • Emphasise the importance of continuous learning and personal growth.
  • Support team members in exploring new technologies, tools, and methodologies.
  • Embrace challenges as opportunities for learning and growth.
  • Create a team environment where individuals feel empowered to voice ideas and opinions.
  • Encourage a “raise your hand” mindset, where seeking help, sharing insights, and suggesting improvements is welcomed.
  • Lead by example and engage with authenticity in all interactions.
  • Provide a safe space for honest feedback and constructive conversations.
  • Value authenticity over conformity, allowing team members to express their true selves.
  • Offer opportunities for skills development, training, and career progression for both team leads and members.
  • Provide mentorship and support to help team members achieve their career goals.

    • Closing Date : 31 July 2025

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