72 Data Science jobs in Western Cape

• Develop and maintain executive-level dashboards and reports using Power BI
• Leverage Databricks for data processing, analysis, and insight generation
• Extract, transform, and manage large datasets using SQL
• Translate complex data into actionable insights for leadership teams across South Africa and the broader African region

• Proven experience working in enterprise-scale environments
• Strong business acumen with a focus on decision-support analytics
• Ability to communicate insights clearly to C-level stakeholders

SWATX Cape Town, Western Cape, South Africa

SWATX Cape Town, Western Cape, South Africa

3 weeks ago Be among the first 25 applicants

SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities:

• Develop and implement the overall data science vision, strategy, and framework to align with organizational goals
• Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning
• Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights
• Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency
• Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges
• Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team's methodologies
• Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth
• Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies
  
  
  

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field
• A minimum of 7+ years of experience in data science or analytics, with 3+ years in a leadership role managing data science teams
• Proficient in programming languages such as Python, R, and experience with big data technologies (e.g., Hadoop, Spark)
• Deep understanding of machine learning techniques, statistical modeling, and advanced analytics methodologies
• Proven track record of successfully leading and delivering large-scale data science projects that drive business value
• Expertise in data visualization tools (e.g., Tableau, Power BI) for effectively communicating complex analyses
• Strong project management skills and ability to lead teams in a fast-paced environment
• Excellent analytical and strategic thinking skills, with a focus on results
• Outstanding communication and interpersonal skills, with the ability to convey technical information to non-technical stakeholders in English and Arabic
  
  

• Certified Data Scientist (CDS)
• Microsoft Certified: Azure Data Scientist Associate
• Google Cloud Professional Data Engineer

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Information Technology
• Industries IT Services and IT Consulting

Referrals increase your chances of interviewing at SWATX by 2x

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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.

The Company We Keep:
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 to apply for the Statistical Data Scientist, Advanced Data Science role at Zindi

Join to apply for the Statistical Data Scientist, Advanced Data Science role at Zindi

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About Us

Advanced Data Science Pty (Ltd) is a boutique data science consultancy specialising in predictive and prescriptive analytics. A big part of the role will be predictive analytics using time series forecasting and statistical inference.

About Us

Advanced Data Science Pty (Ltd) is a boutique data science consultancy specialising in predictive and prescriptive analytics. A big part of the role will be predictive analytics using time series forecasting and statistical inference.

Advanced Data Science is a remote-first company. Periodic travel to clients (in Johannesburg or Cape Town) might be required from time to time.

About The Role

The role of Statistical Data Science is to blend problem solving, statistics, and software engineering.

The idea of translating business problems into statistical problems must appeal to you.

We are seeking a candidate that enjoy Research and Development and is willing to improve his personal capability to stay abreast of new developments in Data Science. This role will include client interaction and you will be expected to take ownership of your solution and collaborate with key

stakeholders to obtain the necessary business acumen. You will need to work closely with your colleagues who will mentor and support you where needed. We will expect that you develop statistical and machine learning models which provide actionable insights, identify trends, and accurately measure performance. The position will help you grow as a data scientist by exposing you to different aspects and challenges of the role.

Must-haves

• Postgraduate in Statistics, Analytics or Operational Research.
• Formal courses in multivariate statistics, (glm) regression theory, machine learning, and a Bayesian course.
• Confidence in your statistical knowledge and ability to apply it.
• R or Python Programming languages. (You must ideally be very proficient in at least one of these languages).
• Ability and interest to learn how to write robust, reusable and testable code.
• Experience and use of Git based technologies. (Use of a GUI is fine).
• Some prior work experience would be an advantage: internships, holiday work or fulltime employment.
• Ability to collaborate effectively within team context.
• Self-motivated and driven with ability to work independently.
  
  

• Experience in Time Series Forecasting
• Experience with mathematical optimisation
• Experience with simulation
• Experience with STAN or another probabilistic language
• Experience in analytical webapp development (R’s Shiny or Python’s Dash)
• Data wrangling / SQL development / Database Design
  
  

• Seniority level Entry level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries IT Services and IT Consulting

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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.

• 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.

• Kafka
• Java
• Git
• Vertica
• Grafana
• Elasticsearch
• gPRC
• Python
• Jupyter
• Docker

• 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)

• 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.

Desired Skills:

• Artificial Intelligence
• Data Science
• Database Design
• Java
• Machine Learning
• Programming
• Python

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Date 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 .

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.

Press Tab to Move to Skip to Content Link

Select how often (in days) to receive an alert:

Date 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 by November 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 .

UWC Sport Bellville, Western Cape, South Africa

Join to apply for the Research Chair: Applied Agricultural and Food Data Science role at UWC Sport

UWC Sport Bellville, Western Cape, South Africa

1 day ago Be among the first 25 applicants

Join to apply for the Research Chair: Applied Agricultural and Food Data Science role at UWC Sport

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Title of Position

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

Main Campus - Bellville, WC ZA (Primary)

Closing Date

22/6/2025

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 September 2025.

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, 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.
  
  

• 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.
  
  

• Seniority level Mid-Senior level

• Employment type Contract

• Job function Research, Analyst, and Information Technology

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