Associate Director, RWE Data Scientist-Gaithersburg, MD

Do you have expertise in and a passion for Medical Affairs in Oncology? Would you like to apply your expertise to impact the Associate Director, RWE Data Scientist role at a company that follows the science and turns ideas into life-changing medicines? Then AstraZeneca might be the place for you!

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big, and collaborating to make the impossible a reality. If you are swift to action, confident in your leadership, willing to collaborate, and curious about what science can achieve, then you’re our kind of person.

AstraZeneca’s vision in Oncology is to help patients by redefining the cancer treatment paradigm, with the 2030 oncology ambition to have medicines that can potentially treat at least half of all cancers. Our broad pipeline of next-generation medicines is focused principally on four disease areas: breast, lung, liver, ovarian, and hematological cancers. In addition to these tumor types, we are targeting cancers through five key platforms: immunotherapy, the genetic drivers of cancer and resistance, DNA damage repair, HER2, and antibody-drug conjugates, all underpinned by personalized healthcare and biomarker technologies.

The Role

The ideal candidate for this role will bring a proven track record of delivering value through the utilization of routinely collected data from healthcare settings, providing health analytics and insights in various contexts, including Public Health, Pharmaceutical Research and Development, and Commercial/Payer sectors.They will collaborate with colleagues in Epidemiology and Statistics to provide scientific and technical guidance on study design, real-world (RW) data selection, and best practices in RW data utilization. The role will promote best practices in Real-World Data Science across multiple domains and stakeholder groups.

Typical Accountabilities

• Collaborate with Epidemiology and HEOR teams to maximize the value derived from a variety of real-world data sources, including EMR, claims, and primary observational data.

• Support stakeholders within Medical Affairs in providing access to analytical tools and developing visual analytics to enable self-serving applications for end customers.

• Provide clear technical input, options, and direction toRWD analysis and utilization supporting RWE and insights generation. 

• Maintain a strong insight into the capabilities of in-house RWD to facilitate data source selection for RWE and insights generation.

• Help build a capability that becomes a source of sustained competitive advantage for AstraZeneca in identifying, acquiring, integrating, and mining diverse RW data from multiple geographic and healthcare system sources to support evidence generation and real-world studies.

Education, Qualifications, Skills, and Experience

Essential:

• PhD or MS in data science or other advanced degree in life sciences such as epidemiology, or other training/work in Medical/Health Informatics/Biostatistics, or a related field.

• Expertise in data analysis, data mining, data visualization, methods development and application using statistical languages such as R, SAS, SQL, or Python.

• Expertise in advanced visualization platform and visual analytics development, such as Power BI and R Shiny.

• Experience in real-world evidence and familiarity with health economics, epidemiology, observational study methodologies, and quantitative sciences such as health outcome modeling.

• Expertise in EMR/Health IT, disease registries, and insurance claims databases.

• Experience in Statistical Analysis Plan (SAP) generation and execution for observational studies.

Desirable:

• Expertise in clinical data standards, medical terminologies, and controlled vocabularies used in healthcare data and ontologies (ICD-9/10, NDC, HCPCS).

• Experience in supporting pharmacoepidemiology studies with a proven track record of advancing approaches with data science.

• Expertise in data mining approaches within healthcare settings to generate insights from routinely collected healthcare data.

• A history of patient care or equivalent background in a patient care setting that allows the candidate to bring a medical perspective into real-world evidence generation and observational studies.

• Demonstrated ability to build long-term relationships with stakeholders, understanding relevant scientific and business challenges at a deep level and translating those into a program of informatics activities that deliver defined value.

• Ability to lead and manage multi-disciplinary data science projects.

• Strong track record of delivering large, cross-functional projects.

• Experience working in a global organization and delivering global solutions.

• Familiarity with the use of Machine Learning and Artificial Intelligence in the generation of hypotheses within Real-World Data.

The annual base salary (or hourly rate of compensation) for this position ranges from $112,000-$168,000. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.  In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles) or to receive a retirement contribution (hourly roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.