Senior Data Scientist (Contract) GautengHybrid ISB8300189

Our client is looking for the following candidate to join a dynamic Data Science and Engineering team at the Group IT Hub South Africa delivering domain- and resort-overarching analytical capabilities to the global Group.

In this role you will act as a significant enabler for integrating horizontal data usage across an advanced Data Analytics Platform generating measurable business value through robust resilient and fully compliant data products.

• Advanced Analytics & MLOps Leadership: Extensive experience designing solutioning and implementing end-to-end data products predictive models and MLOps pipelines within secure cloud environments.

• Technical Leadership: Serve as a functional expert working completely independently to guide engineering teams run comprehensive code/design reviews and translate ambiguous business requests into scalable data science epics and user stories.

• Data Integration & Architecture: Solid understanding of big data architecture streaming data patterns (e.g. Kafka) and data workflows to drive target cloud architecture migrations while ensuring 100% data protection compliance.

Position Details:

• Contract Dates:to

• Location: Midrand / Menlyn / Rosslyn / Home Office Rotation

• Role Group: DevOps Role Name: Data Science and Engineering

• Level: Senior

Qualifications & Experience:

• Relevant IT Business or Engineering degree or equivalent practical experience.

• Minimum 7 years of experience in IT architecture solution design or related technical data leadership roles.

• Proven record of delivering complex enterprise data solutions with measurable business impact in Agile and DevOps environments.

Essential Skills & Technologies:

Data Science & Machine Learning Architecture:

• Proven experience designing and solutioning end-to-end data products predictive models and real-time analytics dashboards in cloud environments (Azure).

• Strong understanding of machine learning architecture principles model deployment patterns MLOps pipelines and data integration standards.

• Ability to evaluate emerging AI/ML technologies and recommend innovations aligned with global manufacturing and quality goals.

Data Engineering & Governance:

• Solid knowledge of big data architecture streaming data patterns (such as Kafka) data governance and compliance frameworks.

• Experience managing data team planning task allocation and driving continuous value delivery within cross-functional squads.

• Strong communication and storytelling skills to explain complex algorithmic models to non-technical business audiences.

Advantageous Skills:

• Expertise in the Azure cloud data stack with secondary knowledge of AWS or Google Cloud.

• Proficiency in Python data science ecosystems and automation scripting.

• Experience with API development and microservices for deploying machine learning models.

• Knowledge of infrastructure-as-code tools specifically for data workspaces such as Terraform or ARM templates.

• Deep understanding of business intelligence tools streaming analytics platforms and data governance frameworks.

• Direct experience acting as a scrum master or agile facilitator to optimize velocity and manage the product backlog.

• Relevant industry certifications (e.g. Azure Data Scientist Associate Azure Solutions Architect Expert).

• Experience working in globally distributed teams and multicultural environments.

Key Responsibilities:

• Technical Guidance: Guide a team of engineers to design and build scalable secure and maintainable advanced analytics solutions and process mining use cases.

• Model Lifecycle Management: Provide technical direction throughout the model development lifecycle conducting design reviews and architectural risk assessments.

• Collaboration & Delivery: Collaborate closely with product owners data engineers developers and operations to ensure strategic alignment and successful data product delivery.

• Standards & Best Practices: Define technical standards data science best practices and reusable analytics components that align with information and data protection rules.

• R&D and Prototyping: Evaluate emerging AI/ML tools and support the development of proof-of-concepts and machine learning prototypes to validate advanced analytical approaches.

• Pipeline Management: Take technical responsibility for data pipelines defining technical stacks toolbox parameters and guiding target architecture migrations on the Cloud Data Hub (CDH).

• Agile Optimization: Contribute to the continuous improvement of data workflows MLOps tools and agile delivery methodologies including managing team backlogs and scrum ceremonies.

Who This Role Would Suit:

This role is ideal for a seasoned Senior Data Scientist or Data Solutions Architect who thrives at the intersection of technical engineering and high-level stakeholder storytelling.

It is tailor-made for an expert who is equally comfortable deep-tuning machine learning deployment patterns as they are establishing data governance and compliance pipelines across complex enterprise domains.

You are a completely independent professional who excels at taking vague cross-border requirements and conducting the deep investigative work necessary to build robust self-service analytical assets.

You possess exceptional communication and negotiation skills enabling you to influence project direction and gain buy-in across diverse organizational departments without exercising direct command.

If you are looking to champion secure cutting-edge AI/ML innovations within a massive global data landscape this role offers an elite space to scale your impact.

Applicants based outside of Gauteng must be willing to relocate. Please note that relocation to the province will be at the candidates own cost.

Eligibility & Legal

• Citizenship: South African citizens and residents are preferred.

• Work Permits: Candidates with valid work permits will be considered.

• Privacy: By applying you consent to being added to our database and receiving updates until you unsubscribe.

If you do not receive a response within 2 weeks please consider your application unsuccessful.

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