M13 is hiring a
Data Engineer

Summary

Carenostics is seeking an experienced (3-5 years) Data Engineer for a hybrid engineering and analyst role in their rapidly expanding company. The ideal candidate will have experience in data analysis, SQL, and developing large-scale data & analytics solutions. Benefits include competitive salary, benefits, stock options, mentorship from proven leaders, and opportunities for rapid upward mobility.

Requirements

• BA / BS in Computer Science or related field
• 3+ years of experience in data analysis in healthcare data, including EMR and claims data
• Excellent critical thinking and problem-solving skills
• 3+ years of work experience with SQL, data warehouses, data lakes, and relational DBs developing large-scale data & analytics solutions
• 3+ years of experience with advanced SQL (including using Windows functions, CTEs, JSON data, and lateral joins)
• 3+ years of developing data-intensive software using SQL and Python in a production setting (ideally including building and deploying production ML systems on top of SQL databases with Agile methodology)
• Strong foundation in technical and programming skills (esp. Python)
• A ‘can-do’ attitude working in a fast-paced startup

Responsibilities

• Contributing to the ML engineering work for AI ML projects, including database and data quality management, feature extraction, data ingestion, data pipeline, CI/CD, MLOps, and incorporating novel data sources (claims, SDoH)
• Developing and deploying the data pipelines, including delivering results to clinicians to enable feature extraction from raw EHR data and setting up infrastructure for interoperability across institutions
• Researching and developing analytical approaches for identifying, analyzing, and interpreting trends or patterns in healthcare data
• Query, structure, and validate data using SQL
• Database management and optimization, improving the efficiency, robustness, and stability of databases and queries
• Support the head of Data Engineering in building a strong culture of accountability and ownership in their team, instilling best-in-class engineering practices (e.g., testing, code reviews, DevOps-forward ways of working), and enforcing data quality and documentation standards
• Communicate with clinical collaborators on results

Preferred Qualifications

• Experience with developing on cloud platforms (AWS, Azure, GCP)
• 3+ years of experience building data science workflows, from data engineering/to building scalable data pipelines
• Experience working with client-facing technical teams
• Familiarity with standard machine learning packages (SciKitLearn, PyTorch, TensorFlow) and experience with statistical modeling

Benefits

• Competitive salary, benefits (healthcare, 401k), and stock options at startup poised for hyper-growth
• A key player in a mission-driven company tackling one of society’s most significant challenges
• Access to rich healthcare data from leading institutions for developing solutions with immediate real-world impact on tens of millions of patients
• Direct mentorship from proven leaders in healthcare, databases, machine learning, and software engineering
• No relocation required