ACCOUNTABILITIES

• Work with consumers/business users on the definition of the data requirements for intended data solutions.
• Translate unstructured, complex business problems into a data design and solution.
• Profile data to understand provenance, quality, metadata models, ownership, and compliance with internal and external regulatory standards.
• Perform ad hoc wrangling of data (sourcing, extraction, profiling, integration) to support Data Science model generation and business insight.
• Support data engineers in the development of Source to Target pipelines (e.g., ETL design).
• Design and test the quality and performance of derivative data models in reporting and analytics solutions.
• Process requests for compliant access to data.
• Define and manage information lifecycle management in data solutions.
• Provide data understanding (structure, provenance, quality) to Architects, Data Engineers, and Data Scientists to support use in Analytics projects.
• Support IT and business data teams in identifying and managing Critical Data Assets and Elements including Reference, Master, and Metadata.
• Collaborate with Risk, Assurance, Privacy, Information Security, and Regulatory authorities to ensure data and information controls are in place and adhered to.
• Clearly and objectively communicate insights and results, as well as their associated uncertainties and limitations.
• Guide junior Data Analysts – supervise task completion, support in troubleshooting challenges, and contribute to performance evaluation reports.
• Share insight and best practices in community forums supporting capability development.
• Provide domain data expertise (data standards, systems, metadata models, policies, business processes) in at least one domain area (e.g. manufacturing, quality, supply chain) while developing expertise in further domains.
• Supporting the development of best practices for Data Analysis: Methods and Technology: technology evaluation, POCs.
• Working with the senior team on the provision of training and skill development in the best practice of Data Analysis: training materials, FAQs, Playbooks, and integrated operating models.

ESSENTIAL SKILLS/EXPERIENCE

• Undergraduate degree in a Computer Science, Data Science or possibly discipline area (R&D, Finance, HR etc) and cross trained or equivalent number of years of experience
• Experienced at using SQL and at least one of the following: python, R, SAS, MATLAB
• Experience in the pharmaceutical industry or a similar regulated sector
• Proven experience in a data analyst or business role aligned to data and information management role with practical examples of performing data analysis in terms of defining requirements, gleaning critical data elements, defining data quality criteria and checkpoints
• Domain data understanding: the structure, provenance and meaning of the source data crucial to the domain (eg. SAP, Werum Pas|X, Snowflake). Understanding of the business processes in the generation and consumption of data
• A blend of data requirement analysis, data quality analysis, data stewardship skills
• Experience in translating requirements into fit-for-purpose data models, data processing designs, and data profile reports
• Proficient in the use of data modelling technologies
• Proven experience working in multi-skilled, multi-location data teams, working to agile principles
• Experience of Data Analysis enabling tool kits (e.g. python, R, DataIku)
• Competent in applying a risk-based methodology to data and information management
• Experience in the use of metadata cataloguing tools

DESIRABLE SKILLS/EXPERIENCE

• Leading the work of others – task setting, supervision, and coaching of more junior staff
• Post-graduate degree in MIS, Data Management
• Knowledge of C, C++ or C# beneficial
  When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That’s why we work, on average, a minimum of three days per week from the office. But that doesn’t mean we’re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.
  At AstraZeneca, we are driven by our commitment to deliver accelerated growth and make people’s lives better. Our supportive team fosters innovation in cutting-edge science, Lean methodologies, and fast-changing digital technologies. We thrive on challenges and work towards new solutions in an inclusive environment where everyone has the freedom to take ownership.
  Ready to take on this exciting challenge? Apply now

As an Associate Director Data Analyst, you’ll take the lead in data analytics, shaping insights with autonomy and creativity. You’ll have the freedom to drive projects, with senior guidance available for unique challenges. Your role includes mentoring junior team members, ensuring they excel in fundamental data analysis tasks and projects. Join us to elevate our data-driven decisions while fostering the next generation of analysts!