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Senior Manager - Data, Analytics and Artificial Intelligence (Strategy & Transformation) (STF-006)

Job Function

Strategy and Transformation

Job Summary

The Senior Manager –Data, Analytics and Artificial Intelligence is someone who lives and breathes data. This person’s best friends are databases and data governance. Basically, everything data.

He/she is someone who is "T" shaped - With numerous IT related skills, communication skills, strategy skills with a deep specialisation in data analytics. He/she works data analytics projects - from gathering the data to doing up visualisations that aim to provide value to the business.

He/she extracts and integrates data from various sources, and creates advanced models and algorithms suitable for the business use case. He conducts testing on data and AI models, interprets findings from testing, and evaluates model performance for scaling and deployment. He develops compelling and logically structured communication materials to facilitate stakeholder buy-in.

He/she works in a team setting and is proficient in statistics, scripting and programming languages required by the organisation. He is also familiar with the relevant software platforms on which the solution is deployed on.

He/she has strong analytical and critical thinking skills to identify and solve problems. He/she is passionate about analysing and resolving complex business problems, displaying intellectual curiosity towards using data and AI to address business needs and challenges. He/she is a data storyteller, and is able to influence key stakeholders and spearhead a data driven approach to resolve business issues.

Being the leader of the team, he/she must be comfortable with interfacing with the C-suite, making difficult decisions and managing team morale. This person is the point person for all things data in the organisation. He/she must be a superhero and have exceptionally high intelligence quotient, emotional quotient and adversity quotient.

Job Responsibilities/Key Tasks(External)

Operations and Data Analytics
•Design and optimise scalable data workflows with subject matter expertise in data loading patterns, data architecture etc. 
•Develop and maintain robust data pipelines that support both real-time and batch processing
•Extract and integrate data from various sources, developing and scaling models in real-time business conditions. This includes interfacing (via API) between the data layer and application layer.
•Leverage on SQL to ensure efficient data transformation and analytics.
•Integrate diverse data sources (e.g., structured, semi-structured, and unstructured) into unified data architectures that power AI-driven applications and insights.


Build and Assess Models
•Train advanced models and algorithms suitable for business use – •Models include computer vision models, forecasting models, route optimisation etc. 
•Work as a team to ensure data readiness, feature engineering pipelines and reproducibility of experiments

Present Data- driven business value of data science/ AI models
•Translate model performance into clear business value (ROI, cost, efficiency, revenue).
•Oversee executive‑ready dashboards that simplify complex data.
•Set real‑time operational criteria to ensure models deliver measurable impact.
•Lead value‑testing of new models versus legacy processes and brief executives.
•Advise leadership on using unified data architectures for efficiency and advantage.
•Communicate complex and black‑box models clearly to drive trust and adoption.

Leadership
•Champion data quality and governance by implementing validation, lineage tracking, and compliance standards.
•Serve as data engineer, software engineer, cloud engineer, and AI scientist all-in-one

Others
•Undertake any projects or duties as directed by Management (if any)

Job Requirements

  • Familiarity with data manipulation, statistical analysis and machine learning theories. This includes extracting and integration of data from various sources, developing and scaling models in real-time business conditions. This includes interfacing (via API) between the data layer and application layer.
  • Understanding of software engineering practices (e.g. Version Control), containerization, CI/CD pipelines
  • Advanced proficiency in SPARK, Python, Java, SQL, Pandas, Hugging Face, Open AI APIs
  • Advanced proficiency with both full stack software engineering and data engineering with solid experience with working with Azure etc.
  • Familiar with data ethics and governance including best practices on how data should be managed securely
  • Strong leadership and management skills, with the ability to motivate and develop a team.  
  • Excellent communication and interpersonal skills, with the ability to build strong relationships with internal and external stakeholders.  

Professional Qualifications & Relevant Experience

  • Bachelors’ in engineering, Economics, Mathematics, Computer Science or related areas
  • Minimum 8 to 10 years of work experience in a related role dealing with data
  • Experience with deploying models using frameworks like TensorFlow, PyTorch, and extremely familiar with platforms like Azure, Databricks, Fabric

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