Ibotta is seeking a Data Scientist to join our Client Data & Measurement team and contribute to our mission to Make Every Purchase Rewarding. Our team leverages the latest developments and best practices in data science, testing methodologies, and statistics to provide actionable insights to the Client Data and & Measurement teams. As a Data Scientist, you will be responsible for using the latest developments in statistics, machine learning, and data visualizations. Using these skills, you will identify and build strategic opportunities to grow the business, support initiatives, and drive value. In addition, you will be expected to build trustworthy and robust models and methodologies for use throughout the organization. This role will immediately drive impact through the support, guidance, and collaboration with multiple spokes as part of our Hub and Spoke organizational layout.You’ll be able to advance not only your technical skills, but your organizational and leadership skills as well, by contributing to the creation of best practices for the team and company, and learning from the more senior scientists and managers on the team. This position is available in multiple locations: Denver, Colorado - if you are in or willing to relocate to the Denver area, this is a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NY, NC, OH, OK, PA, TN, TX, UT, VA, WA, WI. If you’re not in the Denver metro area or the listed states, relocation reimbursement to Denver is available. Not based in Denver? We will offer a relocation bonus to help make your move to the Mile High City a smooth one. What you will be doing: - Contribute to creating best practices for the team - Initiate and drive collaboration with stakeholders, architects, and data engineers to discover, define, cleanse, and refine the data needed for analysis and modeling - Analyze large and novel datasets to extract actionable insights to inform model development and understand consumer behavior - Inform experimental design to formulate solutions addressing major business challenges and innovation opportunities - Build models using a variety of statistical and machine learning techniques, from selecting the best type of model for the problem to using techniques to measure and optimize model performance - Prepare models for production deployment and monitoring of performance over time - Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere What we are looking for: - 2+ years of progressive experience in a professional data science, machine learning, statistics, or data analysis role, or related experience - Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science, Economics or similar field required; Advanced degree preferred - A passion for driving important decisions using data science and data storytelling - A love of learning and continuous development, including staying at the forefront of the latest advances in data science and machine learning. - Broad-scale community contributions to the fields of data science and machine learning in the way of conference presentations, professional publications, and/or recognized internet presence are a strong plus - Demonstrated knowledge, skills, and abilities in developing and applying a variety of machine learning and statistical algorithms - Demonstrated Python skills. Spark or PySpark experience is a strong plus - Broad and general statistical and mathematical knowledge and skills - Excellent analytical and problem solving skills - Demonstrated knowledge, skills, and abilities in database manipulation, query languages, modeling techniques, and programming according to best practices - graph data schemasExposure to or interest in manipulating complex data distributed systems, and data streams - Exposure to or interest in MLOps a strong plus About Ibotta ("I bought a...") Ibotta (NYSE: IBTA) is a leading performance marketing platform allowing brands to deliver digital promotions to over 200 million consumers through a network of publishers called the Ibotta Performance Network (IPN). The IPN allows marketers to influence what people buy, and where and how often they shop – all while paying only when their campaigns directly result in a sale. American shoppers have earned over $2.6 billion through the IPN since 2012. The largest tech IPO in history to come out of Colorado, Ibotta is headquartered in Denver, and is continually listed as a top place to work by The Denver Post and Inc. Magazine. To learn more about what our Tech teams are doing day to day, visit Building Ibotta on Medium.com. Additional Details: - This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, snacks and occasional meals. - Base compensation range: $110,000 - $130,000. Equity is included in overall compensation package. This compensation range is specific to the United States labor market and may be adjusted based on actual experience. - For the security of our employees and the business, all employees are responsible for the secure handling of data in accordance with our security policies, identifying and reporting phishing attempts, as well as reporting security incidents to the proper channels. - Ibotta is an Equal Opportunity Employer. Ibotta’s employment decisions are made without regard of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected status. - Applicants must be currently authorized to work in the United States on a full-time basis. - Applicants are accepted until the position is filled. #LI-Remote #BI-Remote #BI-Hybrid

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.