Senior Data Scientist - Contract - 6-12 months Gauteng

Hire Resolve is actively recruiting for a Senior Data Scientist - Contract - 6-12 months position in Gauteng. This is an excellent opportunity for professionals in the Data / Business / Analysis / Ai sector looking to advance their careers.

• Experience Level: 7 years • Educational Background: Master or equivalent • Industry Focus: Data / Business / Analysis / Ai • Location Preference: in Gauteng

The Senior Data Scientist - Contract - 6-12 months position is an important role within the Data / Business / Analysis / Ai sector, offering meaningful career development and professional growth opportunities.

This role in Data / Business / Analysis / Ai offers valuable career progression opportunities aligned with your experience level and professional aspirations.

When applying for this Senior Data Scientist - Contract - 6-12 months position, ensure your CV highlights: • Relevant experience matching the 7 years requirement • Educational qualifications in line with Master • Specific achievements in the Data / Business / Analysis / Ai field • Any certifications or specialized training

The Data / Business / Analysis / Ai sector in South Africa continues to show strong demand for skilled professionals. This position represents a valuable opportunity in the current job market.

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A client operating in InsurTech, insurance, automative and fleet management is looking for a Senior Data Scientist to join their team on a contract basis based in Johannesburg, GP.  The Data Scientist is responsible for transforming complex datasets into actionable insights that drive intelligent automation, operational efficiency, cost reduction, and predictive decision-making across the organization. This role supports both optimization and innovation-driven transformation by applying statistical modelling, machine learning, data analytics, and data visualization to key business areas, with a focus on identifying new products and enhancing business value.

Responsibilities: 

Accountabilities (Business Outcomes)

Source, cleanse, and prepare both structured and unstructured data. Develop reusable data models and maintain version-controlled datasets for ongoing analysis.

Design, build, and deploy predictive and prescriptive models for forecasting, anomaly detection, and process optimization. Conduct profiling of stakeholders and transactional volatility. Apply statistical techniques, cluster analysis, and AI algorithms (classification, regression, clustering, NLP, etc.). Conduct exploratory data analysis (EDA) to identify trends, risks, and performance insights. Support AI solution engineers by providing training datasets and defining model evaluation metrics.

Build interactive dashboards and reports using visualization tools to present insights to business stakeholders. Translate complex data findings into actionable business recommendations.

Innovation Enablement

Participate in the Innovation Track, supporting proof-of-concept projects that leverage AI and analytics. Conduct extensive literature reviews to determine the most effective multi-modal classification algorithms. Document methodologies and contribute to an internal data science playbook for repeatable value creation.

Risk and Compliance

Ensure compliance with data governance and privacy frameworks. Build models for predicting risk to enable proactive mitigation. Provide insights into predicting future sales and reducing claims costs.

Customer

Collaborate with software developers and data engineers to establish reliable data pipelines, ensuring data integrity, lineage, and governance. Foster strong relationships with internal and external stakeholders by providing data-driven solutions to their challenges. Participate in cross-functional projects to implement end-to-end solutions.

Organize training sessions and workshops to share knowledge and best practices with the broader organization. Create a culture of ownership and accountability in support of the company's values.

Requirements: 

Master's degree in Data Science, Applied Mathematics, Statistics, or a closely related field (equivalent to NQF Level 9).

Professional certification in Machine Learning, Artificial Intelligence, or Information Management. Doctoral (PhD) degree in Data Science, Applied Mathematics, Statistics, or a related discipline (equivalent to NQF Level 10).

Minimum of 7+ years of experience in data science, analytics, or AI engineering. Proven track record of developing, validating, and deploying predictive models into production environments. Strong proficiency with SQL, APIs, and data libraries. Excellent analytical and logical problem-solving ability. Strong business acumen with the ability to clearly communicate complex insights to non-technical stakeholders. A curiosity-driven and innovation-focused mindset. Proven ability to collaborate effectively within cross-functional teams of developers and engineers.

Exposure to Responsible AI frameworks and data governance standards. Awareness of data privacy, fairness, and responsible AI principles. A passion for continuous learning and the application of emerging technologies.