- Use statistical software (Proficient in R; other software is a plus including SAS, Python, and Stata) to perform data manipulation and analysis consistent with protocols and/or statistical analysis plans related to real world data studies to support the NNI evidence generation plan. These studies will be traditional outcomes research studies, economic evaluations of medicines and will be aimed will target top tier journals.
- Subject matter expert for CDSE in terms of RWD sources and their potential utilization
- Drives innovation across CDSE by implementing the most appropriate analytics techniques to address research questions.
- Keeps updated with newer analytic techniques and platforms, and their adaption into the real-world setting; implement these techniques / platforms and describe the rationale for their implementation in appropriate language for internal stakeholders.
- Find new ways to visualize and communicate data to drive a data driven organization.
- Through ongoing interaction with HQ Data Science and related NNI data teams, drive the development of a data access strategy and sharing of best practice.
- Responsible for guiding the organization on all aspects of oversight of data acquisition to support the business. Physical Requirements 10-20% overnight travel required. Qualifications
- Master's degree from an accredited university in fields such as outcomes research, epidemiology, biostatistics, data science, predictive analytics with 3 years relevant work experience is required; a doctoral degree (PhD, DrPH, ScD) is preferred.
- At least 4 years of experience programming with R or Python in the Data Science field in a professional capacity is required.
- Pharmaceutical industry experience preferred.
- Experience working with U.S. longitudinal RWD assets (e.g., claims, electronic health records, and/or surveys) is required.
- Proficiency with statistical methods (e.g., causal inference, survival analysis, general linear models, etc.); machine learning experience welcome, though not essential
- Highly skilled in using statistical software (e.g., R, SAS, Python, and/or Stata), database query (SQL) preferred.
- Peer-reviewed publication track record is a plus.
- Collaborative approach to problem-solving and ability to plan and multi-task.
- Excellent written and oral communication skills
- Proven results producing visualizations for analytical understanding and communication purposes.
- Experience communicating advanced analysis and models to non-technical audiences.
- Clear passion for using data to generate insights and enable data-driven decision making. We commit to an inclusive recruitment process and equality of opportunity for all our job applicants. At Novo Nordisk we recognize that it is no longer good enough to aspire to be the best company in the world. We need to aspire to be the best company for the world and we know that this is only possible with talented employees with diverse perspectives, backgrounds and cultures. We are therefore committed to creating an inclusive culture that celebrates the diversity of our employees, the patients we serve and communities we operate in. Together, we're life changing. Novo Nordisk is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, protected veteran status or any other characteristic protected by local, state or federal laws, rules or regulations. If you are interested in applying to Novo Nordisk and need special assistance or an accommodation to apply, please call us at This contact is for accommodation requests only and cannot be used to inquire about the status of applications.
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Senior Manager - Princeton, United States - Novo Nordisk
Description
About the Department
The Clinical, Medical and Regulatory (CMR) department at Novo Nordisk is one of the most diverse and collaborative groups within the organization. From health-care-provider interactions and developing and implementing regulatory strategies with the FDA to providing medical education and collecting data to support efficacy and new product development, CMR is involved. The one thing that keeps us all marching to the same beat is our patient-centered focus. At Novo Nordisk, you will help patients around the world. As their needs evolve, so does our challenge to find better and more innovative ways to improve their quality of life. We're changing lives for a living. Are you ready to make a difference?
The Position
Leads the execution of observational research studies through the hands-on analysis of real-world data and application of appropriate data science techniques under the minimal supervision of a group leader; studies support the aligned strategy (defined in the Evidence Generation Plan – EGP) spanning one therapeutic area.
Uses both internal and external real-world data to generate unique disease insights and epidemiological information to improve patient care and support business needs. Drives innovation in RWD analytics by implementing new analytic methods, platforms, and technologies to answer research and business questions, supporting data-driven decision making.
Serves as subject matter expert on real world data sources, their utility and novel analytic methods. Develops and maintains strong internal networks across both NNI and relevant HQ functions such as Data Science, serving as a key contact point into the Clinical Data Science and Evidence (CDSE) Real World Evidence (RWE) team.
Relationships
The Senior Manager reports directly to a Senior Director within the CDSE RWE team. This is a US affiliate role executing on US RWD strategy. There will be a number of contact points across NNI and some contact points into HQ, the latter primarily to ensure establishment and access to data sets and learnings on best practice working with that data.
As a key and visible RWD champion in the US enterprise, he/she will work independently with minimum oversight and direction to conduct RWE studies, engage the broader NNI organization in the utilization of RWD, contribute to product evidence strategies, use of RWD and future investments in RWD.
Essential Functions
