The Data Scientist provides expertise in the creation of research protocols and the assessment and understanding of each database used by Julius Clinical as part of the (statistical) data analysis using existing and de novo real-world databases (e.g, structured and unstructured electronics medical records, insurance claims, patient registries) across the therapeutic areas. The Data Scientist may also provide statistical support for all types of clinical projects. The Data Scientist provides expertise in creation, quality control and maintenance of data science programs, plans and manuals for the creation of analysis tables, models, machine learning applications, and related figures. The Data Scientist will be able to recognize potential statistical issues as they create protocols, data definitions and analyses in either post hoc or a priori settings and will be able to collaborate with internal and external colleagues to address these issues under the direction of the Head of Data Science.
Data Scientist (0,8-1,0 fte)
For our Data Science team, we are looking for a communicative and proactive junior or mid-level Data Scientist.
The Data Science department at Julius Clinical supports the whole organization in their mission to deliver high quality clinical research services, which are rooted in academic excellence. This includes assisting in the design, planning, execution and communication of statistical analyses of clinical trials and real world evidence research. In addition, the Data Science Department supports other departments in the automation of data processing and transformation as well as the monitoring of clinical trials through advanced data analytics and dashboarding.
- Create or advise on study protocols, statistical analysis plans and other project related documents across multiple therapeutic areas in collaboration with internal and external functional experts.
- Execute study plans or protocols using R, Python, SAS, SQL or other statistical programming languages by preparing data, deriving study variables, and performing (statistical) modelling and/or testing.
- Provide Quality Control for (statistical) analysis programs and deliverables.
- Develop (automated) programming scripts for advanced statistical modelling, machine learning, and simulation applications.
- Follow internal and external procedures, best practice guidelines, and regulations. Relevant documents include ISPOR Good Practices for Outcomes Research and ICH-GCP with a focus on E9.
- Collaborate with the Project Team and Data Management to identify and deploy the appropriate data assets, methodologies, and (statistical) techniques to answer complex research
- Support ongoing proposals, ad-hoc requests and complex data investigations.
- Contribute to the development of innovative design and methodologies, including new offerings (e.g., cloud-based solutions, real-world evidence projects and optimization of clinical trial procedures).
- A PhD (with no minimum years of experience) or a Master’s degree (with minimum of 2 years of experience) in Statistics, Epidemiology, Mathematics, Computer Science or Economics;
- Strong background in statistical models, advanced analytics, and programming ideally in a healthcare setting (e.g. pharmaceutical industry, medical research, hospital research, Healthtech/Medtech);
- Advanced programming experience in R, SAS, and/or Python;
- Excellent grasp of current and emerging statistical, machine learning techniques and programming techniques and technologies;
- Deep understanding of how observational data sources (such as electronic health records, registries, national databases, etc) can be used for medical research and applications;
- Ideally some experience with one or more secondary data sources commonly used in the pharmaceutical industry (e.g., prescription level data, patient longitudinal registries, chart reviews);
- Strong communication skills to explain and resolve (statistical) analysis issues, ability to communicate (verbal and written) technical and non-technical information clearly to a diverse audience.
An open and informal culture in an innovative, dynamic environment with inspiring colleagues and good working conditions. An environment where you have room to be creative, take initiative and have direct influence on the way we work. We are located in a beautiful monumental building, close to Slot Zeist and public transportation (e.g. busses and train station Driebergen-Zeist). We are flexible in working from home.
Interested in this position? Send your CV and motivation to email@example.com as soon as possible but no later than 30 May 2023. Phone screens and first round interviews will be held the week of Monday, 5 June, followed by a case study interview the week of 12 June 2023. Final round interviews will take place Monday, 19 June – Wednesday, 21 June with an offer extended the week of Monday, 26 June. A start date as soon as possible is preferred.
If you have further questions, you can contact Brianna Goodale, Head of Data Science, at +01 860 614 4649 after 3pm CET or Merel Schoonmade, Chief People Officer at + 31 (0) 6 282 56723.
Our hiring process
Apply for this position
Send your application to firstname.lastname@example.org
You will receive an invitation for a digital meeting with the line manager and HR.
Interview at the office
You will receive an invitation for an interview at our office with your future colleagues.
If there is a match, you will receive an offer. Welcome aboard!