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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Skills
==========
Data SciencePythonRSQL
Industries
==============
Information Technology (IT)
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