Clinical Data Analyst

About Astellas:

At Astellas we are making treatments that matter to people.

We are tackling the toughest health challenges putting the patient at the heart of every move we make.

Our global vision for Patient Centricity is to support the development of innovative health solutions through a deep understanding of the patient experience. At Astellas, Patient Centricity isn’t a buzzword - it’s a guiding principle for action. We believe all staff have a role to play in creating a patient-centric culture and integrating an awareness of the patient into our everyday working practices, regardless of our role, team or division.

We have developed ground-breaking, innovative medicines in immunology, oncology and urology. Our medicines are extending and saving the lives of cancer patients, making transplantation possible and improving the quality of life for those living with conditions where needs are often overlooked.

We take a patient-focused approach, that allows us to convert brilliant early science into treatments and solutions that directly improve and save patients’ lives.

From lab to clinic to patient, we focus on the most promising science, empower the best talent to pursue it, and develop life-changing solutions alongside the best partners.

The Opportunity:

This role will be responsible for the internal real-world data (RWD) conversion to the OMOP Common Data Model, which includes developing specifications, implementing the conversion process, and ensuring quality control. The individual will actively engage in data handling and troubleshooting, demonstrating strong communication skills and a sense of accountability for assigned tasks.

Hybrid Working:

At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver.

Key activities for this role:

• Participate in the design and implementation of the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) ETL conversions.
• To establish source data QC process standards before OMOP conversion and to ensure the conversion is compliance with OMOP transformation and quality standards.
• Create, maintain, and implement quality documentations, such as ETL specifications.
• To communicate with end users in a timely manner regarding data refresh schedule and status.
• Work closely with the data engineering team to ensure conversions and ETL processes are completed according to schedule.
• Collaborate with the team to identify automation opportunities for improved efficiency in OMOP data conversion and applications using OMOPed data.
• Assist with the planning of OMOP activities and provide inputs for project plans and actively participate in Scrum Agile meetings, including backlog grooming and daily stand-ups.

Essential Knowledge & Experience:

• Extensive experience in SQL, ETL, and data handling experience
• Mastery of the OMOP CDM data structure.
• Ability to document vocabulary mappings and transformations for OMOP ETL development.
• Experience with OHDSI datasets and vocabularies. Familiarity with tools such as Atlas, Prometheus, Rabbit in a Hat, and White Rabbit is a plus.
• Knowledge of ETL processes and databases.
• Familiarity with scheduled jobs, batch procedures, and data pipelines and with Redshift databases and the AWS environment.
• Familiar with standard clinical lexicons, coding systems, and ontologies.
• English conversational and business English.

Preferred Experience:

• Previous experience OMOP AND SQL, ETL, data handling.
• Hands-on experience with data warehousing programming languages, such as Python and Scala.
• Data engineering and data architecture experience in optimizing big data pipelines and ETL solutions.
• Knowledge of data standardization and data quality control.
• Familiarity with Agile development methodology and tools.
• Experience with relational database management systems (RDBMS) such as SQL Server.
• Familiar with Real-World Evidence (RWE) and outcome research workflow.

Education:

• Degree in Data handling or equivalent.

Additional information:

• This is a permanent, full-time position.
• This opportunity is based in the UK, USA, or India.
• The team is based across different locations worldwide.
• This position follows our hybrid working model. The role requires a blend of home and a minimum of 1 day per quarter in our local office. Flexibility may be required in line with business needs. Candidates must be located within a commutable distance of the office.

We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.