Associate Director Data Operations Specialist

As a data operations specialist you will be responsible to drive and streamline our RWE and clinical data flow from oncology clinical trials, providing our partners with FAIR data assets to drive innovation. As part of a cross-functional team of science, data and technology guides you will help shaping our data centricity vision, bringing in your innovative ideas and novel approach to rethink the way we lead, treat, handle and govern data. You will use your understanding on current data gaps to improve/ automate our data flow, setting up standards, vocabularies and workflows, working hand in hand with scientists, our data curators, data governance authorities and data product development teams. You will drive communication, training and education to re-shape cross-functional data culture.

Responsibilities

• Develop logic and write queries to extract specific data elements from clinical trial datasets (from both STDM/ADAM) as well as licensed Real-World Data; 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.
• Document data management processes and procedures and develop and maintain standard operating procedures (SOPs) for data management activities.
• Develop and implement strategies for curating clinical trial data for analysis and reporting.
• Find opportunities for training/ education and drive/ support development of training and communication material.
  

Essential requirements

• PhD or Master's degree in a related field (e.g., Health Informatics, Clinical Research, Bioinformatics) or equivalent experience.
• Proven ability in clinical data management or a similar role.
• 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.
• Proficiency with Python and/or R.
• Excellent data manipulation and analysis skills.
  

Desirable requirements

• Experience with data management tools and platforms
• Experience in project management, coordination of mid-size cross-functional teams 
• Experience with agile/scrum operations and planning as well as usage of Jira, Confluence
• Experience with common biomedical vocabularies (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).