Head of Data Engineering - Clinical

August 21, 2024

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Deep 6 AI

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Deep 6 AI is a leader in precision research software, providing an AI-powered, real-time ecosystem for clinical trial acceleration. The company specializes in precision patient matching by mining millions of patient records, including unstructured data such as physician notes, to quickly identify eligible patients for clinical trials. By eliminating manual data validation and utilizing advanced Natural Language Processing (NLP) technologies, Deep 6 AI optimizes clinical trial design, site selection, and patient recruitment, especially in fields like oncology and precision medicine. Their platform connects over 8,000 researchers and 1,100 facilities, supporting faster and more efficient clinical trials with a focus on real-time patient visibility and participation.

healthcare analytics • unstructured data • data science • artificial intelligence • machine learning

11 - 50 employees

Founded 2015

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💊 Pharmaceuticals

💰 $17M Series A on 2019-11

📋 Description

• Lead the continued development and enhancement of our clinical data ingestion and comprehension pipeline. • Drive the utilization of core principles in development, including observability, scalability, and end-to-end control. • Support the utilization of advanced AI/ML research through the exposure of raw, canonicalized, and comprehended data in analytics platforms. • Establish and maintain key performance metrics to track the effectiveness of data engineering initiatives. • Foster collaboration with internal and external stakeholders to gather feedback and drive continuous improvement. • Enhance Deep 6 AI's reputation as a leader in AI-driven clinical trials acceleration through thought leadership and industry recognition.

🎯 Requirements

• Strong player-coach mentality, with an ability to balance the hands-on needs of leading two groups: data platform (data engineering) and search/enrichment (ML engineering). • Proven record of accomplishment, leading successful large-scale clinical data initiatives within a product-focused environment. • Strong background in applied data engineering and data pipelines, with hands-on experience developing and deploying production-ready models. • Understanding of Software Development Life Cycle and data product development • Experience working with healthcare data, especially HL7 and FHIR. • Deep understanding of streaming data ingestion and ETL processes • Conceptual understanding of ML techniques, particularly NLP (e.g., NER, BERT). • Conceptual understanding of AI techniques like large language models (LLMs), self-learning models (SLMs), and other state-of-the-art approaches. • Experience with database technologies, especially Elasticsearch, PostgreSQL, Amazon Aurora, and DynamoDB. • Demonstrated passion for staying up to date with the latest data engineering and pipeline trends, along with a record of accomplishment of driving innovation.