Associate Director, Data Analytics Engineering

Location: Barcelona, Spain (on-site) - 3 days working from the office and 2 days working from home.

Job Description 

As a data analytics engineer you will be responsible for streamlining our usage of oncology real world and clinical data through the development of processes and tools that enable our data science teams to drive innovation. You will join a cross-functional team of science, data and technology guides, and help shape our data centricity vision, bringing in your innovative ideas and novel approaches to rethink the way we lead, treat, and handle data. You will use your understanding of current data gaps to improve/automate our data flow, set up standards, tools and workflows, working hand in hand with scientists, and data product development teams. 

Responsibilities

• Develop and maintain analytics R packages that streamline patient cohort creation and outcomes analysis. 

• Develop logic and write queries to extract specific data elements from licensed Real-World Data and clinical trial datasets (from both STDM/ADAM); work together with Data Engineering team to develop and implement automated data extraction pipelines. 

• Perform data cleaning and validation tasks to ensure data quality and consistency and work with portfolio-facing data scientists to support data wrangling to meet specific analysis needs. 

Essential requirements 

• PhD or Master's degree in a related field (e.g., Bioinformatics, Analytics, Computer Science) or equivalent experience. 

• Extensive experience with R and proven track record of developing and maintaining R packages. 

• Experience working with SDTM and ADAM data formats as well as oncology real world datasets (e.g., Flatiron, Tempus, SEER, Optum). 

• Deep expertise in common SQL dialects (e.g., Postgres, Spark) and proficiency with other data querying languages. 

• Excellent data manipulation and analysis skills. 

• Experience with working in matrix organizations and leading cross-team projects involving multiple stakeholders. 

Desirable requirements 

• Contributions to open-source analytics packages. 

• Experience with development and maintenance of Python packages. 

• Experience with data management tools and platforms. 

• Experience in project management, coordination of mid-size cross-functional teams. 

• Experience with common biomedical vocabularies (OMOP, Gene Ontology, NCI Thesaurus, ISA-Tab, MeSH, Human Disease Onotolgy, BAO, EFO, Human Phenotype Ontology, others), ontology repositories (NCBO Bioportal, EBI OLS) and common reference databases (e.g. Uniprot, Ensembl, CHEMBL, EntrezGene, ClinicalTrials.gov). 

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.