Verana Health

👥 51-100💰 $150,000,000 Series E about 3 years agoDatabase Biotechnology Analytics Health Care💼 Private Company

Verana Health is a leading digital health data company that transforms healthcare through the power of real-world data. We provide actionable insights derived from an exclusive network encompassing over 20,000 healthcare providers and 70 electronic health record systems. Our proprietary platform, VeraQ™, a clinician-directed and AI-enhanced engine, processes nearly half a billion raw healthcare encounters, ensuring data integrity and fueling our curated datasets, Qdata™. This allows us to connect patient care with clinical research, accelerating drug development and enhancing the quality of care and life for patients. We leverage a robust tech stack including SPF, Organization Schema, CDN JS, Google Apps for Business, Amazon Route 53, and several other technologies to build and maintain our data ecosystem. Our engineering culture prioritizes innovation, collaboration, and rigorous scientific research. We champion continuous learning and value diverse perspectives, reflecting in our inclusive and remote-friendly work environment. Our team is driven by DRIVE: Diversity, Responsibility, Integrity, Voice-of-Customer, and End-Results. Verana Health recently secured a $150 million Series E funding round, further solidifying our position in the market and allowing for continued growth and expansion. We offer numerous benefits and a strong commitment to employee growth and well-being, including flexible work arrangements, generous parental leave, and a substantial learning & wellness stipend. We currently employ 51-100 people across various locations, including our headquarters in San Francisco, with remote opportunities widely available across the US. Join us in revolutionizing healthcare research and making a significant impact on patient lives.

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🔥 Senior Quantitative Scientist (ML/NLP)

Posted about 1 month ago

📍 AZ, CA, CO, CT, FL, GA, IL, LA, MA, MN, NC, NJ, NV, NY, OH, PA, SC, TN, TX, UT , VA, WA, Washington, D.C

🧭 Full-Time

💸 154000.0 - 200000.0 USD per year

🔍 Healthcare

🔧 Requirements

5+ years of hands-on experience with messy data (e.g., electronic health records, outcomes data) and analytical methodologies.
3+ years of hands-on experience with machine learning model implementation & deployment, especially on clinical notes
3+ years of hands-on experience with state-of-the-art natural large language models (e.g., BERT, Longformer, RoBERTa, etc.) in resolving use cases like named entity recognition (NER), text classification, entity relation extraction, etc.
Strong familiarity with programming languages, especially Python, Pyspark, R, SQL.
Strong familiarity with coding platforms, especially Databricks, Amazon Sagemaker, Visual Studio Code
Strong familiarity with unstructured text processing techniques.
Familiarity with clinical datasets and coding systems such as ICD, CPT, and RxNorm.
Ability to work effectively with cross-functional teams.
Clear communication skills and able to deliver internal/external presentations.
Ability to prioritize and manage multiple projects with high attention to detail

💡 Responsibilities

Develop and leverage state-of-the-art advances in natural language processing using pre-trained large language models (LLMs) for analyzing and reasoning over clinical notes and other unstructured data in the context of clinical problems.
Drive cutting-edge research on language modeling with emphasis on scientific accuracy and explainability.
Communicate analysis results via presentations to a multi-disciplinary audience using clear, intuitive visualizations.
Establish and maintain best practices for data exploration, end-to-end model development and deployment lifecycle, and data/code/documentation management
Work on Qdata development to enable commercial projects leveraging real-world data through responsibilities such as creation of study plans, implementation of analyses, development of algorithms, and/or writing of publications.
Collaborate cross-functionally with teams (e.g., Commercial, Product, Medical, Engineering/Technology, etc.) to translate clinical investigation questions into detailed data analytics requirements for internal and external projects.
Provide mentorship and knowledge sharing to team members in standardizing machine learning/natural language processing best practices.

AWSPythonSQLData AnalysisMachine LearningNumpyAlgorithmsData scienceREST APISparkData visualizationData modeling

Posted about 1 month ago

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🔥 Clinical Services Leader

Posted 2 months ago

📍 United States

🧭 Full-Time

💸 110000.0 - 140000.0 USD per year

🔍 Healthcare Consulting

🔧 Requirements

Bachelor's degree in relevant field.
7+ years of consulting experience in MIPS.
Experience with CMS Quality Payment Program.
Guiding clinicians in MIPS reporting.
Project management skills.
Experience in therapeutic areas.

💡 Responsibilities

Stay updated on MIPS regulations and provide guidance.
Offer consulting to assist practices with MIPS.
Partner to ensure compliance with QCDR criteria.
Empower team through skill development.
Monitor project timelines and outcomes.

Project Management

Posted 2 months ago

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🔥 Senior Director, Data and Science (Data Development)

Posted 5 months ago

📍 AZ, CA, CO, CT, FL, GA, IL, LA, MA, MN, NC, NJ, NV, NY, OH, PA, SC, TN, TX, UT, VA, WA, Washington, D.C.

💸 245000 - 275000 USD per year

🔍 Digital Health

🔧 Requirements

Master’s or doctorate in a quantitative discipline such as data science, computer science, machine learning, biostatistics, or biomedical informatics.
10+ years of hands-on experience with state-of-the-art natural language models like BERT and Longformer.
5+ years managing technical teams.
Strong familiarity with programming languages including Python, Pyspark, R, SQL.
Experience with coding platforms such as Databricks, Amazon Sagemaker, and Visual Studio Code.
Familiarity with machine learning approaches for clinical imaging data.
Knowledgeable in clinical datasets derived from EHR systems.
Clear communication skills and ability to present to executive teams.
Ability to work effectively with cross-functional teams and manage multiple initiatives with attention to detail.

💡 Responsibilities

Oversee group that is addressing clinical problems by developing and leveraging natural language processing approaches to analyze and reason over EHR clinical notes.
Utilize deep learning techniques to classify and segment clinical images.
Establish and maintain best practices for data exploration, model development, deployment lifecycle, and data/code/documentation management.
Work on variable and Qdata development with emphasis on scientific accuracy and explainability for commercial projects.
Collaborate cross-functionally with teams such as Commercial, Product, Medical, and Engineering to provide input into data requirements.
Mentor team members in standardizing machine learning and natural language processing best practices.

PythonSQLMachine LearningPeople ManagementData scienceCommunication SkillsCollaboration

Posted 5 months ago

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