Data Scientist

Data Scientist to address immediate project needs and align to our broader strategy of developing a skilled, adaptive, and future-ready workforce. This role focuses on developing our data capabilities, supporting current and future organisational goals.

Job Role:

Support for Ongoing Projects: Assist in data collection, analysis, and preliminary insights to support project timelines and maintain momentum on strategic initiatives.

Scalability of Data Operations To handle routine tasks like data preprocessing, exploratory analysis, and report generation, freeing up senior team members to focus on more complex data modelling and strategic decision-making.

Skill Development and Knowledge Transfer: Promote a learning culture by supporting talent development through mentorship, enabling skill acquisition for apprentices and fostering knowledge transfer within the team.

Adaptation to Emerging Trends: Leverage apprentices training in the latest data science techniques to drive innovation, introducing fresh ideas aligned with emerging trends in AI, machine learning, and predictive analytics.

Key Responsibilities:

Data Analysis and Modeling

• Collect, clean, and preprocess large sets of structured and unstructured data from various sources (e.g., user behavior, educational content, performance assessments).
• Apply statistical analysis, machine learning, and predictive modeling techniques to derive insights that enhance educational solutions.
• Develop and refine recommendation systems, predictive models for student performance, and personalized learning pathways.
• Collaborate with stakeholders to design experiments (A/B testing) and analyze the impact of interventions.

Data Visualization

• Create compelling visualizations to communicate findings to technical and non-technical stakeholders, including educators, product managers, and executives.
• Use data storytelling to drive decision-making and improve user engagement.

Collaboration and Communication

• Work with product, engineering, and UX teams to integrate data-driven insights into the development of learning tools and applications.
• Present data findings to internal teams and clients to showcase the impact of data-driven decisions.

Algorithm Development

• Design and improve algorithms that personalize learning content and optimize student outcomes based on user interaction and performance data.
• Continuously refine data collection and processing techniques for improved accuracy and usability.

Note: This is a 6 months attachment with potential for conversion to full time.