Lead Consultant - Analytics Engineering (Model Environments)

us Analytium; Southampton; On-site; GBP 65,000 - 95,000; Full time

Benefits offered by this job

Discretionary annual bonus scheme

Job summary

Analytium, a boutique UK data and analytics consultancy, seeks a role focused on governance of the ungoverned script estate within credit risk environments.

You will lead estate discovery, capture lineage, and industrialise data pipelines while working with risk modelling stakeholders. Occasional travel to Hampshire base and European clients is expected.

Qualifications

• Strong practical SAS capability across Base SAS, macro language, PROC SQL and Enterprise Guide.
• Hands-on Python experience with production-grade scripts/notebooks.
• Databricks experience including Delta Lake, notebooks and cluster behaviour.
• Credit risk modelling knowledge (IFRS 9, IRB, PD, LGD, EAD, stress testing).
• Experience using AI-assisted tools to automate parts of work and explain fixes.

Responsibilities

• Perform estate discovery, own lineage and evidence capture for governance.
• Industrialise data pipelines and evidence rationalisation for audits.
• Work with credit risk, modelling and model risk stakeholders and run workshops.
• Produce outputs clients will act on and maintain client-facing assessment outputs.

Skills

Client-facing communication

Written English

AI-assisted tooling experience

Model governance and validation

Estate discovery & lineage

Tools

SAS

Python

Databricks

Airflow

dbt

Databricks Workflows

Job description

Description

About us

Analytium is a boutique UK data and analytics consultancy - 14 people, 150 projects delivered for 50 clients. We are embedded in a UK tier-one bank, modernising one of the largest SAS estates in the country, because we build our own accelerators and we work AI-first.

Why this role exists

Banks are increasingly asking us a harder question than "can you migrate this" - they are asking "can you make our modelling environment governed, repeatable and defensible". This role focuses primarily on the ungoverned script estate and bringing governance to it. That means walking into a credit risk estate nobody fully understands and producing conclusions that survive a model validation review. The person will do estate discovery, own lineage and evidence capture, bring model lifecycle discipline, industrialise data pipelines, evidence rationalisation decisions so they survive audit, and work directly with credit risk, modelling and model risk stakeholders.

Requirements

Required Qualifications

• Strong practical SAS capability across Base SAS, macro language, PROC SQL, and Enterprise Guide, including the ability to reverse-engineer undocumented code.
• Working-strength Python experience, with the software engineering discipline to take notebooks or scripts to production-grade.
• Hands-on Databricks experience, including Delta Lake, notebooks, and cluster behaviour.
• Credit risk modelling knowledge including IFRS 9, IRB, PD, LGD, EAD, capital, stress testing, or model monitoring.
• Track record of shipping work where an AI coding tool did most of the typing, with the ability to explain what you needed to fix.
• Experience automating part of your own work using AI-assisted ways of working.
• Client-facing experience, including running workshops and writing outputs clients will act on, together with strong written English for client-facing assessment output.
• Able to travel occasionally to the Hampshire base and for possible European client travel.

Preferred Qualifications

• Experience conducting formal estate assessment, discovery, or technical due diligence work.
• Experience with MLOps or model lifecycle tooling such as MLflow, model registries, or feature stores.
• Experience with workflow orchestration tools such as Airflow, dbt, or Databricks Workflows.
• Experience with data product or data mesh operating models.
• Knowledge of European banking or EU regulatory frameworks.
• Experience with Teradata and/or PySpark.

Benefits

• Discretionary annual bonus scheme