Managing Consultant at AND Digital aligning data and AI strategies with business goals. Guiding clients on data value and AI integration within their operations in the UK.
Responsibilities
Defining clear, value driven data and AI strategies that align with business goals, ensuring clients invest in the right problems, not just the newest tech.
Guiding clients on how to treat data as a high value asset, ensuring data quality and architecture can actually support scalable AI.
Evaluating client problems, and designing solutions that solve these problems, mapping out the required process and architecture to succeed.
Recommending modern measurement frameworks that track the ROI of AI implementations and traditional digital services alike.
Getting ‘hands on’ and digging into large data sets to deliver commercial insight.
Conducting technical feasibility studies to determine if a use case is plausible, cost-effective, and technically viable (Build vs. Buy analysis).
Designing the target operating models and upskilling programs that embed AI into the fabric of daily business operations.
Leading the conversation on data and AI governance, ensuring that adoption is safe, unbiased, transparent, and compliant with emerging global regulations.
Understanding of how LLMOps, Vector Databases, and RAG (Retrieval Augmented Generation) architectures integrate with traditional Lakehouse environments (Snowflake/Databricks).
Proficiency across the data lifecycle, from ingestion (ETL/ELT) to visualisation (Tableau/PowerBI/Looker) and advanced governance (Collibra/Alation).
Proven experience in professional services, comfortably guiding C-Suite clients and leadership teams through transformation.
Requirements
Defining clear, value driven data and AI strategies that align with business goals, ensuring clients invest in the right problems, not just the newest tech.
Guiding clients on how to treat data as a high value asset, ensuring data quality and architecture can actually support scalable AI.
Evaluating client problems, and designing solutions that solve these problems, mapping out the required process and architecture to succeed.
Recommending modern measurement frameworks that track the ROI of AI implementations and traditional digital services alike.
Getting ‘hands on’ and digging into large data sets to deliver commercial insight.
Conducting technical feasibility studies to determine if a use case is plausible, cost-effective, and technically viable (Build vs. Buy analysis).
Designing the target operating models and upskilling programs that embed AI into the fabric of daily business operations.
Leading the conversation on data and AI governance, ensuring that adoption is safe, unbiased, transparent, and compliant with emerging global regulations.
Understanding of how LLMOps, Vector Databases, and RAG (Retrieval Augmented Generation) architectures integrate with traditional Lakehouse environments (Snowflake/Databricks).
Proficiency across the data lifecycle, from ingestion (ETL/ELT) to visualisation (Tableau/PowerBI/Looker) and advanced governance (Collibra/Alation).
Proven experience in professional services, comfortably guiding C-Suite clients and leadership teams through transformation.
Benefits
26 days holiday allowance + bank holidays
Flexible bank holidays
12 ‘Wonder, Share, Delight’ days per year which can be used for upskilling, volunteering, personal well being
Annual budget for training and upskilling
Share scheme
A £1000 flexifund to use on a personalised list of benefits such Gym membership, Cycle to Work Scheme, Health, dental and optical cash plan
Private medical insurance
6% employer pension contribution, when you contribute 2%
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