Lasa Health

Lasa Health has been awarded a Small Business Innovation Research (SBIR) grant from the National Science Foundation and has participated in accelerator programs with Techstars Founders Catalyst, Springboard Enterprise, and StartUp Health.. Utilize natural language processing techniques to extract valuable information from unstructured clinical text data and enhance predictive modeling capabilities.. Strong proficiency in Python programming and experience with data science libraries such as TensorFlow, PyTorch, Pandas, and scikit-learn.. Familiarity with natural language processing (NLP) techniques and tools for analyzing unstructured clinical text data.. Flexible hybrid work arrangements with option to join the collaborative environment of our coworking space in Boulder, Colorado.

data scientist

About Lasa HealthLasa Health is a healthtech startup developing AI/ML tools to support clinicians in the diagnosis and management of pelvic pain disorders. Founder, Margaret Melville, suffered from chronic pelvic pain for over a decade and visited 25 doctors before getting a diagnosis. Lasa Health has been awarded a Small Business Innovation Research (SBIR) grant from the National Science Foundation and has participated in accelerator programs with Techstars Founders Catalyst, Springboard Enterprise, and StartUp Health. Position OverviewLasa Health is seeking a talented and driven Data Scientist to join our interdisciplinary team focused on developing clinical decision support tools for the diagnosis and management of chronic pelvic pain disorders. As a Data Scientist at Lasa Health, you will be instrumental in leveraging advanced analytics and machine learning methodologies to analyze complex healthcare data sets, design predictive models, and develop clinical decision support systems. This role presents a unique opportunity to contribute to cutting-edge research while making a tangible impact on patient care in women’s health. Key Responsibilities<ul><li>Develop and implement machine learning algorithms and predictive models to identify undiagnosed chronic pelvic pain patients and provide personalized clinical recommendations.</li><li>Collaborate with cross-functional teams to analyze and preprocess healthcare data, including electronic health records (EHRs), demographic data, and clinical notes, to extract actionable insights.</li><li>Utilize natural language processing techniques to extract valuable information from unstructured clinical text data and enhance predictive modeling capabilities.</li><li>Work closely with clinicians and domain experts to validate model outputs, refine algorithms, and ensure clinical relevance and accuracy.</li><li>Evaluate machine learning model performance, conduct statistical analyses, and iterate on model designs to optimize predictive accuracy and clinical utility.</li><li>Collaborate with external partners, including health systems, to leverage proprietary data sets and clinical expertise in model development and validation.</li><li>Stay abreast of advancements in data science, machine learning, and healthcare informatics, and contribute to the integration of emerging technologies into our platform.</li></ul> Qualifications<ul><li>Master's or PhD degree in Computer Science, Statistics, Physics, Mathematics, Data Science, or a related quantitative field.</li><li>Proven experience in machine learning engineering, data analysis, and predictive model deployment, with a focus on healthcare applications preferred. (ML engineering is essential for success in this position)</li><li>Strong proficiency in Python programming and experience with data science libraries such as TensorFlow, PyTorch, Pandas, and scikit-learn.</li><li>Familiarity with natural language processing (NLP) techniques and tools for analyzing unstructured clinical text data.</li><li>Excellent analytical and problem-solving skills, with the ability to translate complex healthcare data into actionable insights.</li><li>Effective communication skills and the ability to collaborate effectively with cross-functional teams, including clinicians and domain experts.</li><li>Prior experience working with electronic health record (EHR) data and knowledge of healthcare data standards (e.g., HL7, FHIR) is a plus.</li><li>Passion for improving patient outcomes and advancing healthcare through innovative technology solutions.</li></ul> Why join Lasa Health?<ul><li>Work alongside a diverse and talented team of professionals committed to making a meaningful impact in women's health.</li><li>Opportunity to contribute to cutting-edge research and development projects leveraging advanced analytics and machine learning techniques.</li><li>Collaborative and dynamic work environment with opportunities for professional growth and career advancement.</li><li>Flexible hybrid work arrangements with option to join the collaborative environment of our coworking space in Boulder, Colorado.</li></ul> If you're excited about the prospect of pushing the boundaries of healthcare technology through data science, we'd love to hear from you. Join us at Lasa Health and contribute to building the next generation of healthcare solutions! Application InstructionsTo apply, please submit your resume, a cover letter outlining your qualifications and interest in the position, and any relevant work samples or portfolio links demonstrating your expertise in data science and machine learning. Application Link: https://forms.gle/uPPcRMakRXMtx55cA Lasa Health is committed to fostering an inclusive and diverse workplace. We encourage individuals from all backgrounds and experiences to apply. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.

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