Job Description

We are seeking a highly skilled and motivated Digital Health Data Engineer to join a large-name pharma company. This role focuses on analyzing multimodal time-series data from biosensors (such as accelerometers, ECG, PPG, and EEG) and developing advanced data pipelines to support cutting-edge digital health applications. The ideal candidate will possess expertise in Python, cloud-native platforms (AWS, Azure, GCP), machine learning, and familiarity with generative AI (Gen AI) and large language models (LLMs). The role will focus on the development of digital biomarkers and driving innovation to improve healthcare outcomes.

Key Responsibilities:

• Analyze, integrate, and interpret multimodal time-series data from various biosensors (e.g., accelerometer, ECG, PPG, EEG) to derive insights for digital health applications.
• Leverage large language models (LLMs) and foundation models to develop innovative features and solutions in the digital health domain.
• Design, build, and maintain efficient data pipelines that enable seamless integration and processing of large-scale datasets.
• Lead EDA for clinical studies, ensuring fast and actionable insights to support decision-making.
• Present results, insights, and technical solutions through reports, presentations, and technical documentation.

Required Skills and Experience:

• Bachelor's degree with 5+ years of industry experience or Master's degree with 3+ years of industry experience in Computer Science, Data Science, Bioinformatics, or a related quantitative field.
• Experience analyzing multimodal time-series data from biosensors (such as accelerometers, ECG, PPG, and EEG) and developing advanced data pipelines to support cutting-edge digital health applications.
• Strong expertise in Python, with the ability to mentor and support the team in solving complex programming challenges.
• Proficiency in SQL, PySpark, Dask, and working with relational and cloud databases (e.g., PostgreSQL, Redshift).
• Experience working with physiological signal processing, digital health solutions, and bioinformatics applications.
• Familiarity with cloud technologies (AWS, Azure, GCP) and a solid understanding of healthcare systems and digital health technologies.

Nice to Have:

• Experience with large language models and their applications in digital health.
• Experience as a first author on publications related to digital health or data science in well-known journals.
• Experience in FDA submissions, validation, and working within Good Automated Manufacturing Practice (GxP) environments.

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