Job Description & Summary
We are hiring Data & AI Consultants into our Technology Consulting practice. You will deliver client-facing engagements across analytics, BI, data engineering, data governance, data science, AI and workflow automation, in sectors including financial services, public sector, healthcare and life sciences. You do not need to meet every requirement to apply.
Join a Dynamic Team Driving Change
Our Technology Consulting team is part our wider Consulting and Advisory services, made up of both industry leads and subject matter experts driving change and innovation across this ever-growing department. Our consultants possess transferable skills and collaborate across various teams within the Consulting, Advisory department, applying expertise in project management, stakeholder management, communication and process improvement to drive impactful results.
As a Data & AI Consultant, you will work alongside clients across diverse sectors, using your technical, analytical and consulting skills to deliver practical data and AI solutions. The role is hybrid, with client-site presence required where needed.
Role Tracks
The role spans the following Data & AI tracks. Candidates are expected to bring depth in one or more, not all. You may also work across tracks depending on client need (for example, a data engineering engagement may include governance and quality work).
Data Analytics, BI and Reporting
Data Engineering and Analytics Engineering
Data Science, AI and Advanced Analytics
Data Governance, Data Quality and Data Management
Automation and AI-enabled Workflow
Roles and Responsibilities
Responsibilities vary by track and grade, but typically include:
Working with clients to understand business problems and translate them into data, analytics, BI, engineering, governance or automation outputs.
Building dashboards, data pipelines, models, governance artefacts or automation solutions, depending on track.
Profiling, validating and improving the quality of client data.
Preparing client-ready deliverables, documentation and handover materials.
Running client workshops and working sessions.
Managing assigned tasks or workstreams and flagging risks and issues.
Additional expectations at Assistant Manager and Manager:
Lead small teams or workstreams and review junior outputs.
Manage day-to-day client stakeholders.
(Manager) Contribute to proposals, propositions, reusable assets and the development of new Data & AI work.
Skills and Experience
Education and Certifications
Degree or equivalent experience in a relevant discipline such as Data Science, Computer Science, Engineering, Information Systems, Mathematics, Statistics, Economics, Business Analytics or a related field.
Proficiency in at least one programming language (e.g., SQL, Python, R).
Experience, Skills and Competencies
We are looking for candidates with experience in one or more Data & AI disciplines. Candidates do not need to have experience across every area listed below. We are particularly interested in people who combine technical depth with strong communication skills and an interest in client-facing consulting.
Core experience and skills
2–8 years in data, analytics, BI, engineering, data science, AI, automation or governance.
Degree or equivalent experience in a relevant discipline (e.g. Data Science, Computer Science, Engineering, Mathematics, Statistics, Economics, Business Analytics).
Proficiency in SQL and at least one of Python, R, DAX or Power Query.
Strong analytical and problem-solving skills with messy or incomplete data.
Ability to translate business requirements into clear data or technical outputs.
Strong written and verbal communication, including explaining technical content to non-technical audiences.
Interest in client-facing consulting.
Sector experience in financial services, public sector, healthcare or life sciences is useful but not required.
You should have depth in at least one of the following.
Data Analytics, BI and Reporting
Building dashboards and reporting using Power BI, Tableau, Qlik or similar.
Defining KPIs and reporting requirements with business stakeholders.
Power BI semantic modelling using DAX and Power Query.
Analysing data to identify trends, risks and recommendations.
Data Engineering and Analytics Engineering
Building data pipelines and ETL / ELT workflows.
Working with at least one cloud data platform (e.g. Azure, Microsoft Fabric, Databricks, Snowflake).
Designing data models for reporting, analytics or reconciliation.
Implementing data quality checks and technical documentation; exposure to version control and CI/CD is useful.
Data Science, AI and Advanced Analytics
Applying statistical, predictive or machine learning techniques to business problems using Python or R.
Experience across forecasting, classification, optimisation, NLP or GenAI-enabled analysis.
Translating model outputs into business recommendations.
Awareness of model performance, explainability and responsible AI.
Data Governance, Data Quality and Data Management
Profiling, cleansing, validating and remediating data.
Defining data quality rules, dictionaries, metadata and lineage.
Supporting data ownership and stewardship models.
Contributing to data migration, regulatory reporting or remediation projects.
Automation and AI-enabled Workflow
Identifying opportunities to automate reporting, reconciliation or operational processes.
Building solutions using Power Automate, Power Apps, UiPath, Python or VBA.
Mapping current and future-state processes with business users.
Supporting AI-enabled use cases such as document processing, extraction, classification or triage.
