ROLE SUMMARY

The Senior Associate, Digital Quantitative Sciences applies technical, software development and analytical expertise to support the research, development, and deployment of novel digital biomarkers into clinical trials. The successful candidate will inform the selection of sensors and wearable devices, write code to ingest data from these devices, implement the analytics pipelines for combining data from multiple sources, and develop novel digital biomarkers by using advanced signal processing and AI/machine learning techniques. They will also provide subject matter expertise to help advance the research and development of novel digital endpoints and manage the data processing efforts for analytical and clinical validations in collaboration with internal as well as external partners.

This role sits in Pfizer’s AI/ML, Quantitative & Digital Sciences (AQDS) team within Global Biometrics and Data Management, Pfizer Research & Development, leveraging multi-modal data, digital measures, and the power of quantitative science to inform trial designs, support clinical and regulatory strategy and build patient-centric health solutions. The successful candidate will partner closely with Translational Clinical Sciences, Biomeasures, Endpoints & Study Technology team to develop novel measures that advance drug development.

ROLE RESPONSIBILITIES

• Use structured and unstructured data to develop digital biomarkers by implementing novel signal processing and machine learning workflows
• Participate in study design to ensure data meets modeling needs
• Prepare, clean, and filter sensor and clinical data for processing
• Design and build digital endpoint pipelines, implement new algorithms, as well as enhance existing algorithms
• Evaluate algorithm performance and lead verification and validation testing
• Supports algorithm specification documents as well regulatory submissions
• Collaborate with partners in Pfizer Digital to translate algorithm code and insights into product assets
• Develop software tools and scripts at scale to support data analysis and interpretation pipelines
• Integrate and summarize large-scale data and information across multiple scientific, translational, and clinical domains
• Communicate effectively with team members, external experts, and regulatory authorities

QUALIFICATIONS

Basic Qualifications

• M.S. in Biomedical Engineering, Electrical Engineering, Computer Science, Data Science, Biostatistics, or equivalent degree
• Minimum of 1+ year/s of work experience, preferably in a laboratory science, biotech or clinical trial environment
• Technical knowledge through coursework and/or demonstrated application in signal processing, statistics and machine learning
• Superior computational skills: SAS, R, Python, or equivalent, with a knowledge of a variety of commercial packages such as scikit-learn, pandas, pytorch
• Expertise in feature engineering and AI/machine learning

Preferred Qualifications

• Expertise in analyzing physiological sensor signals from sensors and wearable devices, time and frequency domain signal processing, e.g., accelerometer, gyroscope, ECG, CGM, voice
• Knowledge of time series analysis methodologies such as Fourier or wavelet transforms
• Familiarity with cloud technologies (AWS, Google Cloud, Azure)
• Familiarity in setting up and using agile software development, and source control tools, e.g., git
• Excellent communication (written and verbal) and presentation skills
• Experience with Python package development
• Experience working in medical technology or pharmaceutical industries is a plus
• Strong publication record is a plus

Please apply by sending your CV and a motivational letter in English