Head of Clinical Data Science — Vaccines & Immune Therapies (V&I)

At AstraZeneca this is where bold science meetsrealworld Vaccines & Immune Therapies we turncuttingedgeideas into transformative medicines for some of the worlds most complex diseases.We directlyimpactthe lives of populations around the world by turning our ambition to prevent disease intoa reality. With an agile mindset and the strength of a global brand wechallengeand change how things are done.

Werebuilding anorganisationthat resets expectations of what a biopharmaceutical company can beopening new ways to work pioneering novel methods and bringing unexpected teams together.

Our Clinical Data Science team partners directly with clinical biometrics and science teamsacrossresearch anddevelopment. We apply machine learninglarge language modelspredictivemodellingand advancedvisualisationsto acceleratedevelopment end to end.Nowwerelooking for aHead of Data Scienceto lead this team and the TherapeuticAreadata sciencestrategy.

Accountabilities:

AsHead ofData Science for V&I you will define thedata sciencestrategyfor the TA and lead delivery of ahighimpact portfolio spanning clinical and operational/business data. You will set direction inspire and develop a team of data scientists and act as the TAs senior spokesperson for data scienceadvising leaders shaping investments and ensuring our work translates into clear actionable insights for the business and for patients.

You will cultivate strong partnerships acrossResearch & Development ITMedicaland Commercialas well as other data science groups and manage external collaborations with vendors and academic partners.Youllalso champion scientificaccuracyand software engineering best practices to ensure robust reproducible and scalable delivery.

Whatyoulldo

• Set the TA strategy: Define and deliver the V&I data science strategy across clinical and operational/business domains aligning to TA goals and strategy.

• Grow impact and pipeline:Identifyandprioritisenew applications of data science in V&I; translate business problems into analytics questions and deliver solutions that inform decisions and predict outcomes.

• Lead a highperforming team: Line manage and provide inspirational leadership to data scientists at varied career stages; cultivate an inclusivelearningorientedculture.

• Be the TAs data science voice: Serve as key expert and spokesperson; advise senior stakeholders on innovative analytics generative AI and related technologies clearly communicating insights uncertainty and limitations.

• Elevate standards: Drive adoption of best practices in model developmentMLOps validation documentation and data governance; define and implementTAspecifictraining.

• Partner and influence: Build effective collaborations across internal data science groups; shape and manage external partnerships and vendors to deliver value at speed and scale.

• Steer investments: Influence budgets and resourcing tomaximiseportfolio outcomes; contribute to and lead strategic initiatives across the TA.

• Represent the function: Share AZs work at internal forums and external conferences strengthening our scientific presence.

Essentialrequirements

• PhD or MScin a relevant discipline (e.g. statistics computer science mathematics engineering physics) or equivalent experience.

• Proven data science leadershipwith endtoend delivery: data collection and preprocessing modelling for business and clinical problems anddecisionorienteddatavisualisation.

• Significant experiencein drawing conclusions from analysis and presenting analysis results in a succinct fashion to senior stakeholders along with recommended actions

• Knowledge of data analytic and visualization tools such as R Python Spotfire or Tableau.

• Experience working with database systems (egSQL NoSQL graph)

• Proven experience in leading and managing colleagues

• Experience in influencing and controlling budgets

• Excellent written and verbal communication skills

Desirablerequirements

• Masters degreeina quantitative fieldsuch as mathematics computer science engineering physics statistics or economics.

• Life sciences or healthcareexperience especially within clinical development or biometrics.

• Experienceoperatinginhighperformance computing or cloudenvironments.

• Success in acomplex globalorganisation.

• Experience indata miningmachine learninglarge languagemodelsand/oroperations research; strong fundamentals instatistics and algebra.

• Demonstratedproblemsolvingaptitude and bias to action.
  

Why AstraZeneca