If you are looking for a more fulfilling role in professional services, at Grant Thornton, we do things differently. We value fresh thinking, collaboration and diversity, building an inclusive working environment open to all. We are here to support you in the development of your career, provide flexibility where required and respect and value your experience.

Roles and Responsibilities

As a Data & AI Consultant, you will work as part of client-facing delivery teams across data analytics, BI, data engineering, data science, AI, automation and data governance engagements. Responsibilities will vary depending on grade, experience and role track, but may include:

· Working with clients to understand business problems, gather requirements and identify relevant data sources.

· Developing data, analytics, BI, engineering, automation or AI-enabled solutions that address client needs.

· Profiling, validating, cleansing and transforming data to improve quality, consistency and usability.

· Building dashboards, reports, semantic models and management information outputs using appropriate BI tools.

· Designing and developing data pipelines, ETL / ELT workflows, data models and data platform components.

· Applying statistical, predictive or machine learning techniques to support client analytics use cases.

· Supporting AI, NLP, GenAI or automation use cases where relevant to client requirements.

· Defining data quality rules, data dictionaries, metadata, lineage and governance documentation.

· Translating technical analysis and data outputs into clear findings, recommendations and client-ready deliverables.

· Preparing technical documentation, process flows, design specifications, testing outputs and handover materials.

· Participating in client workshops, working sessions and project meetings.

· Managing assigned tasks or workstreams, including planning, tracking progress and escalating risks or issues.

· Working with multi-disciplinary teams across Consulting, Technology, Risk, Financial Services and other Grant Thornton service lines.

· Supporting project delivery activities, including status reporting, quality review and stakeholder updates.

· Supporting business development activity, including proposal inputs, credentials, solution materials and client research.

· Keeping up to date with developments in data, analytics, AI, cloud platforms, BI tools and automation technologies.

· Leading small teams or workstreams across analytics, BI, data engineering, governance, AI or automation projects.

· Reviewing outputs prepared by junior team members and providing coaching and feedback.

· Managing client stakeholders day to day and supporting senior team members in client relationship management.

· Contributing to project planning, delivery management, budgeting and resourcing.

· Helping to develop reusable assets, templates, methods and accelerators for the Data & AI team.

· Identifying opportunities to expand existing client work or develop new Data & AI propositions.

Education and Qualifications

· 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).

Core experience and competencies

· Between 2 and 8 years of experience in data, analytics, BI, data engineering, data science, AI, automation, data governance or a related field.

· Strong analytical and problem-solving skills, with experience working with complex, incomplete or inconsistent datasets.

· Proficiency in SQL and experience working with structured data.

· Experience with at least one programming, scripting or analytical language, such as Python, R, SQL, DAX, Power Query or similar.

· Ability to gather business requirements and translate them into clear data, analytics, reporting or technical outputs.

· Experience preparing client-ready outputs, including reports, dashboards, analysis, documentation, presentations or technical deliverables.

· Strong written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.

· Ability to manage competing priorities, work to deadlines and contribute effectively across multiple workstreams.

· Interest in working in a client-facing consulting environment.

· Experience working with Agile or delivery management tools such as Azure DevOps, JIRA, MS Project or similar is beneficial.

· Experience in consulting, professional services, financial services, banking, insurance, asset management, healthcare, life sciences, public sector or other data-intensive environments is preferred.

· Experience supporting business development, proposals, client presentations or solution development is beneficial, particularly for Assistant Manager and Manager candidates.

· For Manager candidates, experience leading small teams or workstreams, reviewing junior team outputs and managing client stakeholders day to day is preferred.

Data Analytics, BI and Reporting

Candidates with a BI or analytics background may bring experience in some of the following areas:

· Developing dashboards, reports and management information using Power BI, Tableau, Qlik, Excel or similar tools.

· Defining KPIs, reporting requirements and data visualisation approaches with business stakeholders.

· Building Power BI semantic models, measures and calculations using DAX and Power Query.

· Preparing recurring reporting packs, automated dashboards and self-service analytics outputs.

· Analysing data to identify trends, exceptions, risks, opportunities and practical recommendations.

· Improving the quality, consistency and usability of client reporting.

· Supporting report governance, access management, refresh processes and documentation.

Data Engineering and Analytics Engineering

Candidates with a data engineering or analytics engineering background may bring experience in some of the following areas:

· Developing data pipelines and ETL / ELT workflows across databases, cloud platforms and reporting environments.

· Using SQL, Python or similar tools to ingest, transform, validate and structure data.

· Working with relational databases, data warehouses, data lakes, lakehouses or cloud data platforms.

· Designing data models to support reporting, analytics, reconciliation or downstream business processes.

· Experience with technologies such as Azure, AWS, GCP, Microsoft Fabric, Databricks, Snowflake, Oracle, SQL Server, IBM DB2, Teradata or similar.

· Implementing data quality checks, reconciliations, automated controls and exception reporting.

· Creating technical documentation, data lineage, data mappings and handover materials.

· Exposure to version control, testing, DevOps or CI/CD practices is beneficial.

Data Science, AI and Advanced Analytics

Candidates with a data science, AI or advanced analytics background may bring experience in some of the following areas:

· Applying statistical, predictive or machine learning techniques to business problems.

· Using Python, R or similar tools for exploratory analysis, modelling, feature engineering and model evaluation.

· Experience with forecasting, classification, clustering, optimisation, anomaly detection, NLP or GenAI-enabled analysis.

· Translating model outputs and analytical findings into practical business recommendations.

· Supporting AI or machine learning use cases from discovery through to testing, deployment or adoption.

· Understanding of model performance, model limitations, explainability and responsible AI principles.

· Experience with common data science libraries, notebooks, cloud AI services or ML platforms is beneficial.

Data Governance, Data Quality and Data Management

Candidates with a data governance or data management background may bring experience in some of the following areas:

· Profiling, cleansing, validating, reconciling and remediating data.

· Defining data quality rules, controls, issue logs and remediation plans.

· Developing data dictionaries, business glossaries, metadata, data mappings and lineage documentation.

· Supporting data ownership, stewardship and governance operating models.

· Contributing to data migration, system implementation, regulatory reporting or data remediation projects.

· Helping clients improve confidence in data used for reporting, analytics and operational decision-making.

· Awareness of data protection, regulatory, risk or control requirements is beneficial.

Automation and AI-enabled Workflow

Candidates with an automation or workflow improvement background may bring experience in some of the following areas:

· Identifying opportunities to automate manual reporting, reconciliation, data preparation or operational processes.

· Designing and building solutions using Power Automate, Power Apps, UiPath, VBA, Python or similar tools.

· Mapping current-state and future-state processes with business stakeholders.

· Supporting AI-enabled workflow use cases such as document processing, data extraction, classification, triage or decision support.

· Creating process documentation, control documentation, user guides and handover materials.

· Working with business users to test, refine and adopt automation solutions.

Benefits:

Our reward and benefits are designed to create an environment where our people can flourish. We are committed to building a culture where our people have access to the necessary benefits to help promote a healthy lifestyle and thrive.