002ARC - Advanced Analytics Engineer

This role focuses on building the analytical foundation of the platform through Python
based analytical constructs and computational logic that enable AI systems to interpret
structured datasets and provide reliable, deterministic answers through an interactive
interface.
You will work closely with AI engineers to ensure analytical outputs integrate seamlessly
into AI-driven reasoning and insight generation.

What you will do
Build foundational analytical constructs in Python
Develop reusable Python modules that transform structured datasets into analytical
building blocks used across the platform. Examples include:
• period-to-period movement calculations
• variance decomposition and trend analysis
Design structured analytical artefacts for AI reasoning
Create structured analytical outputs that AI systems can reliably interpret. These
structures enable AI systems to generate explainable insights grounded in deterministic
analysis.
Enable deterministic answers through the AI interface
Develop analytical tools that allow the platform’s conversational interface to answer
data questions reliably. This includes building Python functions that can:
• retrieve analytical summaries for a given scope
• identify largest contributors to metric movements
• compute comparisons and trends across reporting periods
These tools allow the AI interface to combine natural language interaction with
deterministic analytical results.
Work with curated datasets from modern data platforms
Collaborate with data platform teams to consume structured datasets from
environments such as Databricks.
Your work focuses on interpreting and analysing datasets, rather than building ingestion
pipelines.
Ensure analytical accuracy and traceability
Implement validation logic to ensure analytical outputs reconcile with underlying
datasets. Design analytical outputs that maintain clear traceability between:• source data
• analytical computations
• AI-generated explanations

Required experience
• Extensive experience building production-grade Python systems that analyse
structured datasets
• Strong SQL skills for working with relational datasets (e.g., Databricks)
• Experience building analytical computations such as aggregations,
comparisons, trend analysis or variance analysis
• Ability to design clear and reusable analytical code structures
• Comfortable using Excel to articulate analytical concepts to business users

Nice to have
• Experience working with financial or insurance datasets
• Familiarity with hierarchical or reporting datasets
• Experience integrating with modern data platforms (e.g. Databricks, Snowflake,
BigQuery)
• Experience preparing structured data for machine learning or AI systems
• Familiarity with causal discovery approaches or graph-based relationship
modelling