Job Description

PBT Group is seeking an experienced and strategic Data Science and Analytics Manager to lead its data-driven transformation journey. This individual will play a pivotal role in developing long-term data science capabilities, building a high-performing team, and ensuring the successful implementation of advanced analytics solutions across the business.
The role demands a strong leader with a deep understanding of data science, machine learning, and operational analytics, along with the ability to align technical initiatives to broader business strategy.
Key Responsibilities:
Data Science Strategy & Implementation

• Lead the implementation of the enterprise-wide data science and analytics strategy in alignment with business goals.
• Identify opportunities for process improvements, automation, and enhanced insights through analytics.
• Collaborate with the General Manager: Data Management and Analytics to define data-specific requirements and strategic goals.
• Guide the development of conceptual models, data pipelines, and advanced analytics solutions that drive business performance.
• Oversee the full data science lifecycle from data ingestion to model production and post-deployment monitoring.
• Translate complex analytical results into clear, actionable business insights.

Team Leadership & Capability Building

• Establish and lead a multidisciplinary team of Data Scientists and Reporting Analysts.
• Foster a collaborative, innovative culture focused on high-impact data work and continuous improvement.
• Conduct technical reviews, provide mentorship, and ensure adherence to best practices in data science methodologies.

Data Engineering & Modelling Collaboration

• Work closely with the Data Engineering team to facilitate robust data ingestion and transformation processes.
• Identify and integrate relevant third-party data sources, including non-traditional inputs such as social media.
• Drive feature engineering, model validation, and implementation of machine learning algorithms and statistical techniques.

Business Engagement & Reporting

• Partner with key stakeholders to identify strategic data needs and deliver impactful solutions.
• Provide concise, insight-driven reporting with appropriate visualisations and business commentary.
• Present findings and recommendations to senior leadership in a clear, data-informed manner.
• Implement controls and improvements in reporting processes to ensure efficiency and accuracy.

Best Practices, Compliance & Risk Management

• Stay abreast of industry trends and innovations in data science and analytics.
• Benchmark internal processes against best practices to identify and close performance gaps.
• Ensure compliance with relevant data governance standards, privacy regulations, and organisational policies.

Financial & Operational Oversight

• Support budgeting and financial planning processes for the data science function.
• Manage expenditure and resources effectively to maximise return on investment.
• Use analytics to identify business improvement opportunities that support financial growth.

Qualifications:
Essential:

• Honours, Master's, or PhD in Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field.
• Relevant certifications in Data Science, Machine Learning, Python, Cloud Platforms (Microsoft, AWS), or Big Data technologies.
• Agile/Project Management certifications such as Scrum or Prince2.

Experience & Skills:
Essential:

• 6-8 years' experience leading data science projects, with at least 5 years in a people management role.
• Proficient in Python or R, SQL, Jupyter Notebooks, and common ML frameworks.
• Strong background in managing large-scale, end-to-end analytics or AI/ML implementations.
• Deep understanding of cloud-based data platforms, large datasets, and data pipelines.
• Advanced skills in statistical modelling, feature engineering, data visualisation, and business storytelling.

Preferred:

• Familiarity with healthcare data, policies, and regulatory frameworks.
• Knowledge of Hadoop, Spark, Kafka, and other big data technologies.

This role presents a unique opportunity to drive high-value innovation through data and make a lasting impact by embedding data science into the core of business operations.

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