Penfield Search Partners
Contact: Jessie Schlomann – firstname.lastname@example.org
Hybrid role – Remote with some travel to Boston
Job Description: Join company as a Senior Manager, Statistics (nonclinical) where you will independently represent Data Science function on projects leading data strategies related to diseases, assets or other areas of interest in company’s ecosystem. You will also lead project delivery directly related to global project teams or other functions. As part of the Data Sciences Institute (DSI), you will report to Director, Statistics. Partner with colleagues from many functions that span R&D (e.g., pharmacology, chemistry, imaging, translational sciences, computational biology, experimental medicine) to Commercial (patient services, sales and marketing, medical information).
As part of DSI, the Statistics and Quantitative Sciences (SQS) at company is looking to add individuals to our team that are team oriented, collaborative, understanding of the statistical programming function, exceptional leaders and innovators. SQS aspires to bring safe and effective medications to the patients with our quantitative skills. We design efficient trials, contribute to clinical development strategies, perform high quality statistical analyses, and pursue operational excellence.
- Work independently and prioritize delivery for projects and with vendors
- Drive and influence project teams towards seamless delivery while allowing and making decisions
- Contribute to asset level strategies to find and address delivery risks
- Have internal and external presence on delivery risks and enabling risk mitigation actions
- Can implement process and best practice changes through delivery risks
- Play a leadership role in the development and review of data science projects and their respective strategies, spanning spontaneous data exploration in individual data sources to designed and planned studies requiring the synthesis of many data archetypes.
- Perform beginning-to-end data analyses, from data strategy to objective formulation, to data exploration and insights, to hypotheses formulation, experimental design, writing analysis plans, data cleaning and curation, executing analysis, to interpretation and preparing reports with documentation.
- Develop and support optimal data handling and data provenance practices utilizing reproducible, interpretable data research approaches.
- Strengthen company’s advanced analytics toolkit by identifying and applying emerging innovative techniques, as well as by advancing the state of the art and developing novel analysis tools as needed.
- Collaborate within a matrix environment with business leaders and scientists to identify and develop appropriate goals for data science work (for example identifying sensitive and endpoints for segmenting patient population, tracking disease progression, quantifying quality of life).
- Provide expertise in concepts related to data acquisition and ingestion working with Data Architecture and IT. Understand respective systems security and provide support for data transparency, disclosure, and governance.
- Strategically connect with company enterprise projects related to the Digital Advisory Board and the Global Data Council.
- Work closely with company statisticians and other quantitative experts to ensure statistical issues in data analysis are addressed as needed.
- Anticipate and communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Propose and implement solutions. Escalate issues to management as appropriate in a timely manner.
- Increase the internal impact of company’s data science work by identifying opportunities across therapeutic or disease areas and business units.
- Increase the external recognition of company’s data science work by participating in conferences, publishing work and developing external collaborations
- PhD (degree in statistics/biostatistics or in other sciences (requirement of Data Science / Quantitative Science: Biostatistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics) with ~3+ years experience in statistical/quantitative statistical environment
- MS (degree in statistics/biostatistics or in other sciences (requirement of Data Science / Quantitative Science: Biostatistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics) with ~6+ years experience
- Experience of clinical study designs, analysis methodology and data interpretation.
- Experience of pharmaceutical industry, overall drug development process with expertise in the interfaces with the Statistics function.
- Experience of FDA and ICH regulations and industry standards applicable to the design, analysis of clinical trials and regulatory submissions.