36 Data Science jobs in Western Cape
Data Science Manager
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SWATX Cape Town, Western Cape, South Africa
Data Science ManagerSWATX is seeking a highly skilled and experienced Data Science Manager to lead our growing data science team. In this strategic role, you will be responsible for overseeing the development and implementation of data-driven solutions to solve complex business challenges. You will mentor and guide a team of data scientists, driving innovation and excellence in analytics and machine learning. If you are a strong leader with a passion for data science and a proven track record of delivering impactful solutions, we invite you to join us.
Responsibilities- Lead and mentor a team of data scientists, providing guidance on best practices in data analysis, machine learning, and statistical modeling
- Develop and execute the data science strategy aligned with business objectives, ensuring that data-driven insights are integrated into decision-making processes
- Oversee the design and implementation of innovative data science projects that drive value for the organization
- Collaborate with cross-functional teams to identify opportunities for leveraging data to improve products, services, and operational efficiency
- Build and maintain strong relationships with stakeholders, understanding their data needs and ensuring timely delivery of insights
- Monitor and evaluate the performance of data science models and adjust strategies as necessary to achieve desired results
- Promote a data-driven culture within the organization by communicating the value of data science initiatives to stakeholders at all levels
- Stay updated on the latest trends and developments in data science and analytics, and integrate new methodologies and tools as appropriate
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
- Proven experience in a data science role, with at least 5+ years of experience, including 2+ years in a managerial or leadership position
- Strong proficiency in programming languages such as Python, R, and experience with data manipulation and analysis libraries
- Solid understanding of machine learning algorithms, statistical methodologies, and data modeling techniques
- Experience with data visualization tools (e.g., Tableau, Power BI) to communicate findings effectively
- Excellent project management skills and ability to prioritize tasks in a fast-paced environment
- Strong analytical and problem-solving skills with attention to detail
- Exceptional communication skills, both verbal and written, in English and Arabic
- Proven capability to drive collaboration across teams and influence senior stakeholders
- Certified Data Scientist (CDS)
- Microsoft Certified: Azure Data Scientist Associate
- Google Cloud Professional Data Engineer
- Mid-Senior level
- Full-time
- Information Technology
- IT Services and IT Consulting
Lead Data Science & DataOps Engineer
Posted 5 days ago
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Job Overview
As Lead Data Science & DataOps Engineer, you will lead our Data Science and DataOps functions, driving technical excellence, strategic alignment, and innovation across projects, ensuring that best practices and processes are followed, and the quality of data science, data ops and dashboarding solutions are maintained. This role requires deep technical expertise in data science, AI/ML, and data engineering, alongside strong leadership and mentoring capabilities. You will ensure quality delivery, scalable architecture, and ethical use of data while building a high-performing team that supports Reach’s strategic priorities.
Key Focus Areas
1. Strategic & Technical Leadership
- Provide strategic direction and technical leadership across Data Science, AI/ML, and DataOps.
- Define and drive a roadmap aligned with organisational goals, with a focus on digital health, impact measurement, and large-scale behaviour change.
- Guide architectural decisions, assess technical risks, and ensure alignment with broader engineering goals.
- Play an active role in shaping Reach's technology strategy and contribute to organisation-wide KPIs.
2. AI/ML Research & Development
- Drive the design, development, and deployment of high-impact AI/ML models (e.g. LLMs, predictive modelling, NLP, recommendation engines).
- Explore and experiment with emerging technologies, algorithms, and tools to push the boundaries of innovation.
- Champion ethical, responsible AI - ensuring fairness, transparency, and accountability in model design and use.
3. DataOps & Infrastructure
- Oversee the design, development, and automation of scalable and secure data pipelines, workflows, and infrastructure.
- Implement data governance, privacy, and compliance standards across data and model operations.
- Collaborate with SRE, MERL and Engineering teams to ensure seamless integration of data workflows.
4. People Leadership & Team Growth
- Build, manage, and mentor a high-performing team across Data Science, AI/ML, and DataOps disciplines
- Promote a culture of learning, knowledge sharing, and psychological safety.
- Support professional development and growth of individuals and the broader function.
5. Collaboration & Cross-Functional Impact
- Collaborate with cross-functional teams including MERL, SxD, Engineering, and
- Implementation to ensure high-quality delivery and impact.
- Provide data-driven insights and support the development of monitoring tools for real-time evaluation.
- Support on technical input for proposals, concept notes, and partnership development.
6. Operational Excellence & Ways of Working
- Champion process improvements, AI/ML and DataOps practices, and reproducibility standards.
- Promote consistent adoption of best practices across all data and model development workflows.
- Take responsibility for risks, delivery timelines, and the quality of technical outputs.
Responsibilities
- Lead end-to-end development of AI/ML and data solutions, from ideation to deployment and monitoring.
- Design experiments, perform impact analyses, and contribute to data strategy for research and delivery teams.
- Drive continuous evaluation and improvement of models and pipelines.
- Manage team resourcing, performance, recruitment, and onboarding.
- Represent the team internally and externally through conferences, stakeholder engagements, and publications
Qualifications
- Relevant degree in a quantitative or technical field (e.g. Computer Science, Engineering, Statistics, Mathematics, Economics) or equivalent experience.
- Strong mathematical background and a proven track record in data science, data engineering, or AI/ML senior roles.
Skills & Experience Required:
- 7+ years of relevant experience, including 3+ years in a senior or leadership role.
- Strong expertise in data science, data engineering, and AI/ML development.
- Hands-on experience with cloud platforms (AWS, GCP, Azure), DataOps and MLOps tools (CI/CD pipelines, model monitoring), and orchestration tools.
- Strong coding skills (Python, Bash, etc.) and experience with distributed computing.
- Excellent communication and stakeholder engagement skills.
- Demonstrated ability to lead cross-functional, multidisciplinary teams.
Desirable:
- Experience with big data technologies (Spark, Hadoop), containerisation (Docker, Kubernetes), and open-source contributions.
- Knowledge of data privacy regulations and ethical frameworks for AI.
Lead data science & dataops engineer
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Lead data science & dataops engineer
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Assistant Professor, Teaching Stream - Data Science
Posted 21 days ago
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Assistant Professor, Teaching Stream - Data ScienceDate Posted: 07/14/2025
Closing Date: 11/17/2025, 11:59PM ET
Req ID: 44011
Job Category: Faculty - Teaching Stream (continuing)
Faculty/Division: Faculty of Arts & Science
Department: Department of Statistical Sciences
Campus: St. George (Downtown Toronto)
Description:
The Department of Statistical Sciences in the Faculty of Arts and Science at the University of Toronto invites applications for a full-time teaching stream position in the area of Statistical Sciences. The appointment will be at the rank of Assistant Professor, Teaching Stream with an anticipated start date of July 1, 2026.
This search aligns with the University’s commitment to strategically and proactively promote diversity among our community members ( Statement on Equity, Diversity & Excellence ). Recognizing that Black, Indigenous, and other Racialized communities have experienced inequities that have developed historically and are ongoing, we strongly welcome and encourage candidates from those communities to apply.
The successful candidate must hold a PhD in Statistics, Computer Science, Data Science, or a closely related discipline by the time of appointment, or shortly thereafter with a demonstrated a strong record of excellence in teaching.
We are seeking candidates whose teaching interests will complement and enhance the department’s strengths in education . Applicants must have teaching experience in statistics, biostatistics, or data science within a degree-granting program, at the undergraduate level for students specializing in statistics or related fields with strong mathematical and computational components. This includes experience in course design, lecture preparation and delivery, curriculum development, and the creation of online educational materials.
Candidates must show a strong commitment to pedagogical excellence and innovation, as evidenced by engagement in teaching-related activities and pedagogical inquiry. A demonstrated interest in advancing teaching practices and curriculum development is essential.
Applicants should have expertise in the application of statistical methods in data science, machine learning, or artificial intelligence. Experience must include the preparation and delivery of course content that incorporates real-world data and applied statistical methods. Furthermore, we prefer that candidates have experience in interdisciplinary collaboration as a statistician or data scientist on projects involving genuine applications of statistical or data science methods.
Preferred qualifications include a demonstrated interest in supervising undergraduate research projects, experience managing large enrolment courses and teaching assistants, and a collaborative approach to course coordination and teaching.
Evidence of excellence in teaching and commitment to pedagogical scholarship should be demonstrated through teaching accomplishments such as teaching awards, peer-reviewed presentations at major conferences, a comprehensive teaching dossier (as outlined in the application instructions below), and strong letters of reference from referees of high standing.
Salary will be commensurate with qualifications and experience.
All qualified candidates are invited to apply online at Academic Jobs Online, and must submit a cover letter; a current curriculum vitae; and a complete teaching dossier to include a teaching statement, sample syllabi and course materials, and teaching evaluations.
E quity, diversity and inclusion are essential to academic excellence as articulated in University of Toronto’s Statement on Equity, Diversity and Excellence . We seek candidates who share these values and who demonstrate throughout the application materials their commitment and efforts to advance equity, diversity, inclusion, and the promotion of a respectful and collegial learning and working environment.
Applicants must also arrange to have three letters of reference (dated, on letterhead and signed ) uploaded through Academic Jobs Online directly by the writers by the closing date. At least one reference letter must primarily address the candidate's teaching.
All applicant materials, including recent signed reference letters, must be received byNovember 17, 2025.
CAUTION : This ad is “posted only” to the U of T faculty job board. Please see the information above for application instructions. Applications submitted via the U of T platform will NOT be considered for this position.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Diversity Statement
The University of Toronto embraces Diversity and is building aculture of belonging that increases our capacity to effectivelyaddress and serve the interests of our global community. Westrongly encourage applications from Indigenous Peoples,Black and racialized persons, women, persons withdisabilities, and people of diverse sexual and gender identities.We value applicants who have demonstrated a commitment toequity, diversity and inclusion and recognize that diverseperspectives, experiences, and expertise are essential tostrengthening our academic mission.
Accessibility Statement
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.
If you require any accommodations at any point during the application and hiring process, please contact .
Senior Software Engineer - Data Science (CH1148)
Posted 5 days ago
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Our client is a medium-sized engineering company based in Stellenbosch, specializes in the design, development, integration, implementation, and support of complex hardware and software systems. The client’s Data Science team is looking for a Senior Software Engineer with strong Data Science expertise to help design and implement cutting-edge machine learning and AI features. These features will unlock powerful insights and real value from the massive volumes of data processed by our large-scale, real-time distributed systems.
In this role, you'll collaborate with a team of highly skilled professionals in a dynamic and innovative environment. You’ll be involved from the very beginning of the product lifecycle— evolving ideas, implementation, all the way to deployment at client sites. This is a rare opportunity to build solutions that have real-world impact while working at the intersection of software engineering and data science.
The ideal candidate is a proactive problem solver who takes full ownership of his/her work and thrives in dynamic environments. You are naturally curious, adaptable and eager to learn. Strong communication skills are essential, as you'll be expected to convey complex technical concepts clearly to both technical peers and non-technical stakeholders. You’ll collaborate closely across multiple teams to tackle challenging, real-world problems—always keeping the end user and support teams in mind to ensure that the features you help build are both impactful and practical.
Required:
- Bachelor’s degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related quantitative field with a focus on data science, AI, or machine learning.
- At least 4 years of hands-on experience in a data science or data-focused software engineering role.
- Proven experience in the training, deployment and operational support of machine learning or AI models in production environments.
- Strong programming skills in Python and/or Java, with a solid understanding of software engineering principles and best practices.
- Proficient in database design and querying, including experience with SQL and working with large datasets.
- Comfortable working in Unix-based environments, including scripting, troubleshooting and networking.
- Experience with data wrangling, feature engineering and model evaluation techniques.
- Experience with version control systems, container technologies, microservice-based architectures, and CI/CD pipelines tailored for machine learning workflows.
Preferred:
- Masters in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field.
- Experience working with real-time or event processing systems, such as Apache Kafka.
- Strong understanding of distributed systems and scalability challenges in big data environments.
- Practical experience with audio processing, NLP, LLM or RAG techniques.
- Experience building and deploying ML services as dynamically scalable microservices.
- Proven ability to mentor junior team members and contribute to technical leadership within a team.
- Background in telecommunications, signal processing or IP networks will be a big bonus.
Tech Stack:
- Kafka
- Java
- Git
- Vertica
- Grafana
- Elasticsearch
- gPRC
- Python
- Jupyter
- Docker
What’s on Offer
- Exciting personal and career growth opportunities.
- A collaborative, relaxed, and innovative work culture.
- The chance to work with state-of-the-art technologies and complex distributed systems.
- Hybrid working (In office 3 Days per week)
Other:
- Only shortlisted candidates will be contacted. Should you not hear from us after 30 days you may consider your application unsuccessful
- Only SA Citizens will be considered
- Please include your current salary and salary expectations.
Assistant professor, teaching stream - data science
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Research Chair: Applied Agricultural and Food Data Science
Posted 1 day ago
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Research Chair: Applied Agricultural and Food Data Science
Post Number
8653
Faculty/Department
University of the Western Cape -> Natural Sciences -> Natural Sciences Faculty Administration
Type of Position
Fixed Term Contract
Length of Contract Period
N/A
Location
Closing Date
15/10/2025
Role Clarification & Key Performance Areas
In the framework of a DAAD-funded project focused on Sustainable and Resilient Food Systems and Applied Agricultural and Food Data Science, the University of the Western Cape (Cape Town, South Africa) is seeking to appoint a Research Chair at the level of Associate Professor/Professor, starting from 1 March 2026.The Chair is funded by the German Academic Exchange Service (DAAD) with funds from the Federal Ministry of Research, Technology and Space (BMFTR).
A key component of this project is the establishment of a Centre of Excellence at the University of the Western Cape, dedicated to sustainable and resilient agri-food systems, as well as applied agricultural and food and nutritional data science. The centre’s primary objective is to further develop the expertise of doctoral students, early-career researchers, and university lecturers through application-oriented and transdisciplinary research in agri-food systems and applied data science. It also aims to enhance teaching methodologies and mentorship programmes within these interdisciplinary fields.
The Centre is established within a German-African university consortium, co-led by the University of Hohenheim and the University of the Western Cape, with the University of Pretoria and the Lilongwe University of Agriculture and Natural Resources as core partners and the University of Mpumalanga as associate partner.
Within the Centre, a Research Chair is created to advance the linkage between agri-food systems research and data science. The Research Chair will, together with the management team, lead and coordinate the activities of the Centre, and serve as a liaison between the Centre and the research groups at the partnering institutions (including the NRF-funded Research Chair on farming systems at the University of Mpumalanga). The duration of the contract position is tied to the project’s duration which ends December 2029.The position is financed by the DAAD with funds from the BMFTR, reporting directly to the Deputy Vice Chancellor responsible for Research and Innovation at the University of the Western Cape.
The successful candidate will be responsible for the following key performance areas:
- Establish and advance an independent research agenda aligned with the Centre’s research themes;
- Strengthen the research profile of the Centre via active participation, postdoctoral and PhD supervision, publications, and innovative contributions;
- Facilitate learning events affiliated to resilient food systems and agri-food data sciences;
- Spearhead the liaison between the Centre and the research groups at the partnering institutions in the consortium with the aim of deepening the synergistic relationships and creating possibilities for creating new opportunities and channels of funding;
- Work with the eResearch Office, the Information and Communication Services (ICS) on Research Data Management (RDM) and High Performance Computing issues related to agri-food systems;
- Facilitate research grants and learning and/or teaching stays for German doctoral students, university lecturers and (young) researchers in South Africa;
- Facilitate regular webinars and seminars on Resilient Food Systems and Agri-Food Data Science;
- Develop mechanisms for long term sustainability of the Centre of Excellence;
- Work with relevant departments on the establishment of agri-food data science short courses for the industry.
- You must be a citizen of an EU member state.
- Applicants (m/f/d) should generally have lived in the Federal Republic of Germany for the last two years before applying. Close contact with a German university is also essential during the period abroad.
- Possession of a Ph.D. in one of the following fields: Data Science, Computer Science, Computer Engineering, or Food Systems/Agriculture with a demonstrated expertise in Data Science applications.
- Experience in teaching undergraduate and postgraduate data science courses at a German University.
- A track record of quality peer-reviewed publications in accredited journals and conferences, and research in data science, preferably in the context of Agri-food Systems.
- A track record of successful postgraduate supervision of both Masters and PhD students in Data Science and/or Agri-food Systems.
- Evidence of international presence in data science related research fields.
- Evidence of leadership experience and ability to work in multinational and multicultural research environments.
The following documents must be submitted with the application:
- a separate description of your research vision for the Centre of Excellence.
- a curriculum vitae including a list of publications.
- contact information for three referees.
- a brief teaching dossier, preferably on data science and food systems related modules including teaching evaluations.
DISCLAIMER: By applying for the position, you consent to the University sharing your application, including curriculum vitae, with University stakeholders to process the application. In line with the University’s commitment to diversifying its workforce, preference will be given to suitably qualified applicants in line with our Employment Equity Targets. The official retirement age at UWC is 65 years. The University reserves the right to not make an appointment, make an appointment at a different level, seek additional candidates and may conduct competency assessments.
#J-18808-LjbffrResearch Chair: Applied Agricultural and Food Data Science
Posted 24 days ago
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In the framework of a DAAD-funded project focused on Sustainable and Resilient Food Systems and Applied Agricultural and Food Data Science, the University of the Western Cape (Cape Town, South Africa) is seeking to appoint a Research Chair at the level of Associate Professor/Professor, starting from 1 March 2026.The Chair is funded by the German Academic Exchange Service (DAAD) with funds from the Federal Ministry of Research, Technology and Space (BMFTR).
A key component of this project is the establishment of a Centre of Excellence at the University of the Western Cape, dedicated to sustainable and resilient agri-food systems, as well as applied agricultural and food and nutritional data science. The centre’s primary objective is to further develop the expertise of doctoral students, early-career researchers, and university lecturers through application-oriented and transdisciplinary research in agri-food systems and applied data science. It also aims to enhance teaching methodologies and mentorship programmes within these interdisciplinary fields.
The Centre is established within a German-African university consortium, co-led by the University of Hohenheim and the University of the Western Cape, with the University of Pretoria and the Lilongwe University of Agriculture and Natural Resources as core partners and the University of Mpumalanga as associate partner.
Within the Centre, a Research Chair is created to advance the linkage between agri-food systems research and data science. The Research Chair will, together with the management team, lead and coordinate the activities of the Centre, and serve as a liaison between the Centre and the research groups at the partnering institutions (including the NRF-funded Research Chair on farming systems at the University of Mpumalanga). The duration of the contract position is tied to the project’s duration which ends December 2029.The position is financed by the DAAD with funds from the BMFTR, reporting directly to the Deputy Vice Chancellor responsible for Research and Innovation at the University of the Western Cape.
The successful candidate will be responsible for the following key performance areas:
- Establish and advance an independent research agenda aligned with the Centre’s research themes;
- Strengthen the research profile of the Centre via active participation, postdoctoral and PhD supervision, publications, and innovative contributions;
- Facilitate learning events affiliated to resilient food systems and agri-food data sciences;
- Spearhead the liaison between the Centre and the research groups at the partnering institutions in the consortium with the aim of deepening the synergistic relationships and creating possibilities for creating new opportunities and channels of funding;
- Work with the eResearch Office, the Information and Communication Services (ICS) on Research Data Management (RDM) and High Performance Computing issues related to agri-food systems;
- Facilitate research grants and learning and/or teaching stays for German doctoral students, university lecturers and (young) researchers in South Africa;
- Facilitate regular webinars and seminars on Resilient Food Systems and Agri-Food Data Science;
- Develop mechanisms for long term sustainability of the Centre of Excellence;
- Work with relevant departments on the establishment of agri-food data science short courses for the industry.
- You must be a citizen of an EU member state.
- Applicants (m/f/d) should generally have lived in the Federal Republic of Germany for the last two years before applying. Close contact with a German university is also essential during the period abroad.
- Possession of a Ph.D. in one of the following fields: Data Science, Computer Science, Computer Engineering, or Food Systems/Agriculture with a demonstrated expertise in Data Science applications.
- Experience in teaching undergraduate and postgraduate data science courses at a German University.
- A track record of quality peer-reviewed publications in accredited journals and conferences, and research in data science, preferably in the context of Agri-food Systems.
- A track record of successful postgraduate supervision of both Masters and PhD students in Data Science and/or Agri-food Systems.
- Evidence of international presence in data science related research fields.
- Evidence of leadership experience and ability to work in multinational and multicultural research environments.
The following documents must be submitted with the application:
- a cover letter outlining your interest.
- a separate description of your research vision for the Centre of Excellence.
- a curriculum vitae including a list of publications.
- contact information for three referees.
- a brief teaching dossier, preferably on data science and food systems related modules including teaching evaluations.
Research chair: applied agricultural and food data science
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