Job Description & Summary
We are hiring an Associate Director to help lead and grow our Data & AI capability within Technology Consulting. You will shape and deliver client engagements across data strategy, analytics, BI, data engineering, data governance, data science, AI and automation. You will lead multi-disciplinary teams, manage senior client relationships, oversee delivery quality and contribute to the continued growth of the practice.
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 at leadership level. Candidates are expected to bring depth in one or more, not all, and the ability to lead specialists across several tracks.
Data Strategy, Operating Model and Transformation
Data Analytics, BI and Reporting Leadership
Data Engineering and Data Platform Leadership
Data Science, AI and Advanced Analytics Leadership
Data Governance, Data Quality and Data Management Leadership
Automation and AI-enabled Workflow Leadership
Roles and Responsibilities
As a Data & AI Consultant at Associate Director level, you will help lead the growth and delivery of Grant Thornton’s Data & AI capability within Technology Consulting. You will work with senior clients and internal teams to shape, sell and deliver Data & AI engagements across analytics, BI, data engineering, data governance, data science, AI and automation.
Responsibilities may include:
Lead client engagements across Data & AI, from shaping and mobilisation through to delivery and implementation support.
Work with senior client stakeholders to understand business priorities and shape practical data-led solutions.
Lead multi-disciplinary delivery teams across analytics, BI, engineering, data science, governance and automation.
Provide quality assurance over technical and business deliverables, and translate technical work into clear recommendations for senior audiences.
Manage delivery planning, risks, issues, dependencies, budgets and engagement economics.
Identify new opportunities and lead proposals, client presentations and commercial responses.
Develop propositions, methodologies, accelerators and reusable assets, and support recruitment and onboarding.
Coach and develop consultants across Data & AI disciplines.
Depending on background and client demand, the Associate Director may also:
Lead data strategy and operating model assessments.
Oversee BI, reporting and dashboard transformation programmes.
Lead data engineering, data platform or migration workstreams.
Shape advanced analytics, machine learning, NLP or GenAI use cases.
Lead data quality, governance, metadata or remediation programmes.
Lead AI-enabled automation and workflow improvement engagements.
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.
A minimum of 8 years’ professional experience in data, analytics, BI, data engineering, data science, AI, automation, data governance, technology consulting or a related field.
Proficiency in at least one programming language such as SQL, R or Python.
Experience, Skills and Competencies
We are looking for an experienced Data & AI professional with strong delivery leadership, client management and technical credibility in one or more Data & AI disciplines. Candidates do not need to have equal depth across every technical area, but should be able to lead multi-disciplinary teams and shape client solutions across data, analytics, AI or governance.
Core experience and leadership skills
- 8+ years in data, analytics, BI, engineering, data science, AI, automation, governance or technology consulting.
- Degree or equivalent experience in a relevant discipline (e.g. Data Science, Computer Science, Engineering, Mathematics, Statistics, Economics, Business Analytics). Advanced degrees are welcome but not required.
- Proven experience leading Data & AI engagements, programmes or teams.
- Strong stakeholder management at senior client level.
- Ability to translate technical work into clear recommendations, business cases and delivery plans.
- Experience managing delivery risks, dependencies, budgets and engagement economics.
- Commercial awareness and experience supporting business development and proposals.
- Experience coaching, developing or leading junior team members.
- Proficiency in at least one of SQL, Python or R.
- Sector experience in financial services, public sector, healthcare or life sciences is beneficial.
Relevant certifications (e.g. Microsoft Certified: Data Analyst Associate, Azure / AWS / GCP, Microsoft Fabric, Databricks, Snowflake, DAMA) are beneficial.
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Track-specific experience
You should have depth in at least one of the following.
Data Strategy, Operating Model and Transformation
- Defining data strategies, roadmaps and business cases.
- Designing data operating models, governance structures and delivery approaches.
- Leading data maturity assessments, discovery phases or mobilisation.
Translating business strategy or regulation into Data & AI initiatives.
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Data Analytics, BI and Reporting Leadership
- Leading BI, reporting and dashboarding delivery.
- Overseeing KPI design, semantic modelling and reporting transformation.
- Providing quality assurance over Power BI, Tableau, Qlik or similar.
Improving reporting governance, controls and adoption.
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Data Engineering and Data Platform Leadership
- Leading the design and delivery of data pipelines, ETL / ELT and platform components.
- Advising on data warehouse, lakehouse and cloud platform approaches (e.g. Azure, Microsoft Fabric, Databricks, Snowflake).
- Overseeing data modelling, quality, reconciliation, lineage and testing.
Providing delivery oversight across engineering teams.
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Data Science, AI and Advanced Analytics Leadership
- Leading statistical, predictive, machine learning, optimisation, NLP or GenAI use cases.
- Advising clients on responsible and practical use of AI.
- Overseeing model design, validation, deployment and monitoring.
Applying responsible AI principles (explainability, fairness, human oversight, data protection); awareness of model risk and AI regulation is beneficial.
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Data Governance, Data Quality and Data Management Leadership
- Designing governance frameworks, ownership models and stewardship approaches.
- Leading data quality assessments, remediation programmes and metadata development.
- Supporting data migration, regulatory reporting or system implementation.
Embedding governance into business and technology processes.
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Automation and AI-enabled Workflow Leadership
- Identifying automation and AI-enabled workflow opportunities across operations, risk, finance, compliance or customer processes.
- Leading delivery using Power Automate, Power Apps, UiPath, Python or similar.
- Advising on AI for document processing, extraction, classification, triage or decision support.
- Moving use cases from proof of concept into sustainable delivery.
