Title: Contract Data Scientist Location: Boston, MA or New York City, NY Hybrid Full-time Job Description: Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine. Here’s a collection of articles about our product, mission, recent funding round, etc. Job Description You will work with the Layer Health ML team applying our existing ML workflow to tailor models for a specific clinical use case. You will design, build, evaluate, and iterate on these models — combining strong data science fundamentals with modern LLM techniques to deliver high-accuracy, production-ready solutions across new clinical domains. This is a high-velocity, high-ownership role for someone who enjoys diving deep into error modes, making targeted improvements, and closing the loop between model performance and real-world impact. This contract will require full-time hours. What you’ll do: - Own end-to-end development of models for specific use cases: Build and iterate using our ML/LLM-powered workflows for new clinical areas, from initial prototyping through production refinement. - Conduct evaluation & error analysis: Own rigorous evaluation of model performance; perform deep error analysis to identify systematic failure modes and drive targeted improvements. - Ship frequent, high-quality updates to models based on data, feedback, and observed edge cases. - Leverage LLM application & tooling: Apply modern LLM techniques (prompting strategies, structured outputs, tool use, eval frameworks) to improve accuracy and robustness. - Support analytics & metrics: Contribute to metrics, reporting, and internal dashboards that track model performance and downstream impact. We look for: - Good data science fundamentals, including knowledge of best practices for evaluating model performance and error analysis. (A proven track record of successful projects in healthcare or clinical applications is a bonus, but not required.) - Familiarity with modern applied LLM techniques and their practical implementations, for example e.g. standard prompting techniques, LLM frameworks, structured output usage, etc. (any experience using these techniques is a bonus). - Solid programming skills in Python. - A strong technical communicator who thrives in a fast-paced environment. - Proactive mindset to identify and solve problems, continuously improving our data science capabilities. - An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML, alongside an awesome team. - Willingness to be hybrid with our team in either our Boston or NYC office 3 days per week. Expected compensation range for this role is $40 - $70/hour. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made. If you are excited about this role, we encourage you to apply even if you don't feel that you meet every single requirement. We're eager to meet people that believe in our mission and can contribute to our team in a variety of ways. We welcome diverse perspectives, rigorous thinking, and fearlessness in challenging the status quo. Join us and help us transform healthcare with AI. Layer Health is committed to foster an environment of inclusion that is free from discrimination. We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.

Role Description Buscamos un(a) Científico(a) de Datos con entre 3 y 5 años de experiencia, responsable de diseñar, desarrollar y optimizar modelos analíticos descriptivos, predictivos y prescriptivos que permitan mejorar la toma de decisiones y generar impactos operacionales tangibles, escalables y repetibles para el negocio. - Diseñar modelos analíticos y seleccionar técnicas, variables, codificaciones y algoritmos adecuados. - Desarrollar el código de los modelos y asegurar su correcto funcionamiento. - Analizar grandes volúmenes de datos para generar insights y apoyar decisiones informadas. - Identificar relaciones entre variables y construir soluciones basadas en analítica descriptiva, predictiva y prescriptiva. - Optimizar modelos para asegurar escalabilidad, repetitividad y eficiencia. - Apoyar el roadmap de modelos y actividades analíticas junto con el líder del equipo. - Liderar el monitoreo, mantenimiento y actualización de los modelos implementados. - Co-liderar el despliegue de modelos en ambientes tecnológicos internos junto con Arquitectura de Datos. - Guiar técnicamente a otros científicos de datos del equipo. Qualifications - Experiencia de 3 a 5 años en ciencia de datos o analítica avanzada. - Al menos 2 años de experiencia en modelación analítica predictiva o prescriptiva. - Manejo de grandes volúmenes de datos y estructuras de datos complejas. - Conocimiento en matemáticas aplicadas, inteligencia artificial, machine learning, reinforcement learning, estadística y econometría. - Experiencia en desarrollo integral de soluciones: extracción, modelamiento, despliegue y reportes. - Manejo de Python, Spark/PySpark, SQL, NoSQL, AWS, Azure, Big Data y APIs LLMs. - Conocimiento medio en CI/CD y calidad de datos. - Deseable participación o reconocimientos en concursos de analítica. Requirements - Pensamiento algorítmico. - Capacidad analítica. - Curiosidad intelectual y aprendizaje continuo. - Orientación al cliente. - Entendimiento del negocio. - Trabajo bajo presión. - Capacidad para liderar y guiar equipos analíticos.

• Design, develop, and deploy advanced AI/ML models and algorithms that improve operational efficiency, forecasting accuracy, and decision intelligence across the Hunter Douglas supply chain. • Conduct data exploration, feature engineering, and model tuning to ensure accuracy, robustness, and business applicability. • Collaborate with business stakeholders to translate complex challenges into data-driven solutions aligned with organizational goals. • Monitor, retrain, and optimize models post-deployment to maintain high performance as data and business conditions evolve. • Apply state-of-the-art methods such as neural networks, reinforcement learning, natural language processing (NLP), and generative AI to tackle diverse business challenges. • Contribute to the AI strategy roadmap, ensuring alignment with Hunter Douglas’s digital transformation initiatives. • Work with data engineers and IT to ensure efficient data pipelines, scalable infrastructure, and model deployment. • Partner with internal and external technical teams, vendors, and consultants to implement and scale AI solutions. • Communicate findings and insights clearly to both technical and non-technical stakeholders through visualizations, presentations, and storytelling. • Stay at the forefront of AI and analytics innovation, evaluating new tools, methodologies, and technologies for potential adoption. • Collaborate with digital product and IT teams to develop and integrate AI-assisted tools and automations within Hunter Douglas’s VIBE platform and data ecosystem. • Experiment with AI coding assistants (e.g., Cursor, GitHub Copilot, OpenAI Codex) to accelerate analytics and model development and improve reproducibility. • Support the creation of custom AI copilots and prompt libraries for use in digital supply chain tools, analytics dashboards, and planning applications. • Partner with the Digital Supply Chain Leader to prototype intelligent process automation for recurring planning, logistics, quality, or operational workflows.

Role Description Apartment List is looking for a Staff Data Scientist to help us attract and match the right renter with the right property at the right time. In this role, you’ll work on some of the most important data science problems across Apartment List. - Work on demand-side renter acquisition and marketing models like User Value Modeling. - Develop supply-side partner models like Supply Value Score. - Focus on ranking, personalization, renter intent, and emerging Pathmaker AI work. - Build zero-to-one models in areas still powered by heuristics and business rules. - Improve existing production ML systems across ranking, personalization, renter intent, and marketplace optimization. - Help shape the Data Science roadmap and partner with various teams to turn ambiguous opportunities into measurable impact. Qualifications - 7+ years of industry experience, or equivalent experience, developing, deploying, and iterating on machine learning models in production. - A degree in Computer Science, Computer Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative field. - Deep proficiency in Python and SQL, with comfort working across the full model development lifecycle. - Familiarity with standard ML libraries and frameworks such as scikit-learn, XGBoost, TensorFlow, PyTorch, or similar tools. - Experience working with cloud platforms; GCP experience is preferred but not required. - Strong technical and theoretical grounding in statistical learning, modeling, experimental design and analysis, and causal inference. - Curiosity, judgment, and a hunger to dig into uncharted territory and make a meaningful impact. Requirements - Apply a strong statistical mindset to model development, experimentation, causal inference, tradeoff analysis, and decision-making. - Lead ambiguous, high-leverage technical work: define scope, evaluate approaches, manage tradeoffs, and align stakeholders around a clear path forward. - Communicate ML opportunities, tradeoffs, and results clearly to technical and non-technical audiences, including senior stakeholders. - Mentor and collaborate with other data scientists, helping raise the quality of our modeling, experimentation, and analytical practice. - Thoughtfully leverage modern AI tools to improve productivity across coding, analysis, documentation, and workflow automation. Benefits - Work on ML systems that directly shape the renter experience, property partner outcomes, and company performance. - Build and own models end-to-end, from ambiguous opportunity through production launch and iteration. - Collaborate with talented, motivated, and intellectually curious colleagues. - Have a strong voice within R&D and across the business, helping shape product, marketplace, and company strategy through data science. - Work in a virtual-first environment that allows you to work from anywhere in the U.S.