Job Summary:
We are seeking a highly skilled and experienced Lead/Principal
Data Scientist/ AI Application / Data Architech/ Data Governance manager to lead complex data/ AI projects and drive strategic insights. This role requires expertise in statistical modeling, machine learning, LLM (optimisation is a plus) and data storytelling to influence business decisions and product strategy. The ideal candidate should have strong build and lead (cross functional) team, the vision to foster data driven culture, a strategic problem solving, and ability to thrive in fast-paced environment perform effectively under pressure.
AI/ML optimization - Key Responsibilities:
• Define and execute the strategic vision for Data Science and Optimisation across multiple business lines.
• Lead, grow, and inspire a team of data scientists and ML&
AI engineers.
• Stress shaping product strategy, influencing executives, and aligning AI initiatives with corporate goals.
• Collaborate with cross-functional teams (Product, Engineering, Marketing, etc.) from different lines of business and presenting to key stakeholders, partners, ...
• Overseeing analytics projects, including data extraction, cleaning, modeling, and interpreting results, while leading senior team members on data-driven solutions
• Mentor and provide technical guidance to senior data scientists.
• Evaluate and recommend new tools, techniques, and technologies to improve analytical capabilities.
• Promote the integrity, accuracy, and usability of data sources and models
Data Scientist - Key Responsibilities:
• Design, develop, and implement advanced statistical models and machine learning algorithms to solve business problems.
• Collaborate with cross-functional teams (Product, Engineering, Marketing, etc.) from different lines of business to understand requirements and deliver actionable insights.
• Execute analytics projects, including data extraction, cleaning, modeling, and interpreting results, while collaborating with senior team members on data-driven solutions
• Translate complex analytical outcomes into clear, business-friendly insights and recommendations.
• Mentor and provide technical guidance to junior data scientists and analysts.
• Evaluate and recommend new tools, techniques, and technologies to improve analytical capabilities.
• Ensure the integrity, accuracy, and usability of data sources and models
Data Architect - Key Responsibilities:
• Design scalable conceptual, logical, and physical data models (OLAP, OLTP, Data Vault, or Star Schema).
• Evaluate and select the right tech stack (e.g., Snowflake, Databricks, BigQuery) and integration tools (dbt, Airflow).
• Optimise complex queries and data pipelines to handle petabyte-scale datasets with minimal latency.
• Lead the transition or optimisation of on-premises legacy systems to modern cloud native architectures.
Data Governance - Key Responsibilities:
• Build and maintain the Data Governance roadmap, including data cataloging, lineage, and metadata management.
• Establish a council of data stewards across departments to drive accountability and standardise definitions.
• Ensure all data practices align with government regulations and internal security protocols.
• Define and monitor Key Performance Indicators (KPIs) for data accuracy, completeness, and timeliness.
• Partner with product and data science teams to ensure governed data is available for modeling and AI initiatives.
• Establish governance policies and processes that ensure data quality, compliance, and trust, following globally recognised principles of data management.
• Embed governance practices into daily operations, making compliance and quality part of the data lifecycle.