The Business Data Analyst is responsible for the data specification, data design and data testing of repeatable, scalable data products which can be easily interpreted by audiences across the business, to drive critical business thinking. The Business Data Analyst will be aligned to the specification and pre-release validation of innovative solutions for the business, as well as curious around existing or new potential data sources which could be integrated into our data products. The Business Data Analyst role leverages cross functional working between Data Engineers and Business Analysts, aligning to a constant appreciation of business impact throughout. The role is an integral part of realizing our ambition to reach predictive and prescriptive analytics, and is split into the following key responsibilities:Data specification and design;Solution based mindset, deep thinking, grounded in business and tech verification of robust end-to-end data flowsDetailed requirements gathering which facilitate delivery of systematized, scalable, engineered data solutionsDocumented specifications that consider the critical data paths, grounded in the business logic and ‘why’Fast iteration builds of feasibility prototypes, considered for specific data features or elementsValidating the most logical way forward, prior to scalable systemisation, through leveraging wider team networkConsulting with the business on demands, furthering only those that align with the most impactful innovationsData structures;Deep knowledge of AbbVie’s data and its structures in context of how those data will be leveraged by data pipelines, data technologies and end business use casesFundamental appreciation of machine learning, predictive analytics and advanced visualisation techniquesSkills and experience in grooming and triaging data entitiesData consultation, focused on the delivery of business decisions through dataDecision modelling (‘what if’ scenario-based logic for enterprise data processing)KPI design and specification iteration, validation and challenge of data/metric logicAbility to interpret and untangle outcomes from complex data for a commercial, decision-making audienceDeep dive data quality assessments and facilitationData governance & quality;Clear prioritisation of most impactful business innovationsEvidence based data validation resulting from data engineering impactsData health check authentication and incident managementData query and complaints management, alongside a stewardship mindset in context of enterprise businessA strong advocate and enforcer of documentationData literacyGains and maintains an intimate understanding of our data and its workflows, with the aim of using its possibilities and limitations in scoping conversations with the businessFacilitates a critical mass of data literacy throughout the business, encouraging that capability wherever possiblePushes for the realisation of better business questions (at the point of request)