JOB DESCRIPTION The Associate Data Scientist supports the Operations Data Science & AI team at UL Solutions in developing predictive models, data-driven and AI solutions for laboratory, field engineering, and accreditation & compliance operations. The role covers the full innovation lifecycle - from ideation and prototyping to implementation and validation - combining hands-on data science with basic data engineering. This is a collaborative, applied role working at the intersection of operations, principal engineering, and global technology and other partners. - Develop and apply machine learning and AI methods to predict test outcomes, automate decision-making, and extract insights from complex operational data across UL Solutions laboratories, field engineering, and compliance operations. - Work with diverse operational data sources including laboratory information systems, legacy databases, sensor data, and structured/unstructured documents. - Collaborate with operations, principal engineering, and technology partners to identify AI opportunities and translate business problems into working solutions. - Support the full innovation lifecycle from ideation and feasibility assessment through prototyping, implementation, validation, and production deployment. - Evaluate and apply emerging AI techniques -- including large language models, retrieval-augmented generation, and computer vision -- where they add value to operational workflows. - Combine scientific methods with business process understanding to ensure solutions are technically sound, operationally relevant, and properly validated. - Perform basic data engineering tasks including data extraction, transformation, and pipeline maintenance to ensure reliable data availability for AI and analytics. - Support innovation management activities by helping develop blueprints and frameworks to systematically identify, evaluate, classify, and prioritize AI and predictive modeling opportunities - contributing to the team's innovation portfolio from early ideation through feasibility validation and implementation readiness. RESPONSIBILITIES - Collect, process, cleanse, and validate data from diverse operational sources for analysis and modeling. - Perform exploratory data analysis on large, complex datasets to identify patterns and determine appropriate analytical techniques. - Build, train, and optimize machine learning models (classification, regression, clustering, time-series) for predictive modeling and other AI use cases. - Explore and prototype AI-driven solutions beyond classical ML, such as NLP, document understanding, or intelligent automation where applicable. - Support feature engineering, model selection, hyperparameter tuning, and model evaluation using established scientific and statistical methods. - Develop and maintain basic ETL workflows and data pipelines to support modeling and reporting needs. - Document model assumptions, limitations, validation results, and alignment with business processes. - Present analysis results, model performance, and recommendations clearly to both technical and non-technical stakeholders. - Stay current with AI and data science developments and assess their applicability to UL Solutions operations. - Contribute to the maturation of data science and AI capabilities across laboratory, field engineering, and compliance operations. QUALIFICATIONS - Minimum of bachelor's degree or equivalent work experience in Data Science, Computer Science, Statistics, Physics, Engineering, or a related quantitative field. - Knowledge of machine learning techniques (clustering, decision trees, random forests, neural networks, regression) and their practical trade-offs. - Python coding skills for data manipulation, analysis, and model development (NumPy, Pandas, Scikit-learn, PyTorch or similar). - Basic understanding of modern AI concepts including large language models, NLP, and retrieval-augmented generation. - Experience querying databases using SQL. - Familiarity with data visualization tools (e.g., Power BI, Matplotlib) to communicate findings. - Basic understanding of data engineering concepts (ETL pipelines, data quality, data integration). - Exposure to cloud platforms (Azure preferred) and version control (Git/GitHub) is a plus. - Strong analytical and problem-solving skills with a hands-on, applied mindset and curiosity for emerging technologies. - Good communication and presentation skills - able to explain technical methods and results to non-technical audiences. - Ability to work in a multidisciplinary team and contribute to strategic goals. - Software engineering skills such as test-driven development, CI/CD practices, API design, or containerization are a plus What you'll experience working for ULS UL Solutions has been pioneering change since 1894 and we're still leading the way. From day one, we've blazed a trail protecting the planet and everyone on it. Our teams have influenced billions of products, plus services, software offerings and more. We break things, burn things and blow things up. All in the name of safety science. That's where you come in - because none of it could happen without you. It takes passion to protect people, problem-solving to safeguard personal data and conviction to make the world a more sustainable place. It takes bold ideas and brilliant minds to build a better world for future generations across the globe. This is more than a job. It's a calling. A passion to use our expertise and play our part in creating a more secure, sustainable world today - and tomorrow. As a member of our safety science community, you'll use your ideas, your energy and your ambition to innovate, challenge and ultimately, help create a safer world. Everyone here is unique. But we're also a global community, working together to help create a safer world. Join UL Solutions and you can connect with the brightest minds in the business, all bringing their distinct perspectives and diverse backgrounds together to deliver real change. Empowering our customers to keep the world safe means thinking ahead. It means investing in training and empowering our people to learn and innovate. At UL Solutions, we help build a better future - one where everyone benefits. Join UL Solutions to be at the center of safety. To learn more about us and the work we do, visit UL.com Total Rewards: We understand compensation is an important factor as you consider the next step in your career. The estimated salary range for this position is $65,000 to $78,000 and is based on multiple factors, including job-related knowledge/skills, experience, geographical location, as well as other factors. This position is eligible for annual bonus compensation with a target payout of 5% of the base salary. This position also provides health benefits such as medical, dental and vision; wellness benefits such as mental and financial health; and retirement savings (401K) commensurate with the standard rewards offered in each individual location or country. We also provide full-time employees with paid time off including vacation (15 days), holiday including floating holidays (12 days) and sick time off (72 hours). #LI-SG2 #LI-Remote ABOUT US A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. UL Solutions delivers testing, inspection and certification services, together with software products and advisory offerings, that support our customers' product innovation and business growth. The UL Mark serves as a recognized symbol of trust in our customers' products and reflects an unwavering commitment to advancing our safety mission. We help our customers innovate, launch new products and services, navigate global markets and complex supply chains, and grow sustainably and responsibly into the future. Our science is your advantage.

• Act as the technical referent for marketing measurement projects across global markets, guiding implementation within established frameworks • Translate business needs into robust analytical solutions in collaboration with consultants and product teams • Support the technical design, execution, and interpretation of models such as MMM, Advance digital Attribution models, and geo-lift tests • Contribute to model deployment and integration into web-based platforms, in collaboration with product and data engineering teams • Ensure consistency and quality across deliverables, promoting repeatable and privacy-first methodologies • Represent technical capabilities in internal conversations and client-facing discussions • Help maintain a knowledge-sharing culture across the team, and mentor junior team members when appropriate.

• Design, develop, and deploy machine learning and predictive analytics models. • Analyze large and complex datasets to identify trends, insights, and business opportunities. • Build scalable data science solutions and optimize model performance. • Collaborate with data engineering and business teams to define project requirements and deliver analytical solutions. • Develop data pipelines, feature engineering processes, and model evaluation frameworks. • Implement AI/ML algorithms for forecasting, classification, recommendation, and automation use cases. • Present analytical findings and recommendations to technical and non-technical stakeholders. • Ensure data quality, governance, and compliance standards are maintained. • Mentor junior data scientists and support best practices across the team. • Stay updated with emerging technologies and advancements in Data Science and AI.

Role Description Quadax, an award-winning leader in healthcare revenue cycle technology, is seeking a Data Science Analyst to join our Team and help us create the best Revenue Cycle Optimization solution in the industry. You’ll use your knowledge of healthcare revenue cycle business objectives to identify necessary data (SQL, Excel, Snowflake), apply appropriate analytics (BI tools, Azure Foundry) and derive strategic insights to achieve the desired business benefits. You’ll work closely with product managers, other data scientists, engineers, and business analysts to ensure clear definition of all requirements and translating them into value. You’ll leverage data insights to optimize the revenue cycle product design and user experience of our Platform. We use PowerBI for visualization, Snowflake for data management & sharing, and Azure Foundry for all modeling. Local candidates preferred. Open to remote employees ONLY in: OH (if residence is outside a reasonably commutable distance), PA, MI, IN, KY, WV, WI, AL, TN, GA, FL, TX, MO, SD, NC. Responsibilities - Ability to analyze complex data sets and create actionable insights - Uses knowledge of business objectives, strategies, and needs to identify opportunities where data can be leveraged to achieve the desired business benefits - Understands current data context, processes and availability, and how current data processes and existing data can be leveraged to achieve the desired benefits - Prepares and analyzes data, including locating, profiling, cleansing, extracting, mapping, importing, transforming, validating, or modeling - Applies query, data exploration and transformation, basic statistical methods, and visualization techniques to create business insights or improve data quality - Performs validation and testing to confirm the accuracy of the information created - Interprets results of analyses, identifies trends and issues, and develops recommendations to support business objectives - Communicates complex information so that it is easy to understand and influences others to take action based on the useful information provided - Facilitates the design and development of product features - Interviews subject matter experts, customers, and other stakeholders to identify and clarify requirements - Establishes rapport with stakeholders and ensures that their questions and concerns are clearly documented - Presents on-time delivery of requirements and user stories/specifications - Supports the creation and maintenance of project documentation - Writes user stories and technical requirements for projects including complex business rules, logic flow diagrams, conditional logic, use cases, and specific workflows Qualifications - Healthcare revenue cycle experience with hospitals, providers, and/or other healthcare delivery organizations - 2+ years of experience working in Data Science - Professional experience with, and more than a basic understanding of AI technology - Proficient in building process flow diagrams and data mapping - Experience with agile development and software development life cycle (SDLC) processes - Proficiency with SQL programming - Extensive experience working in a BI environment and familiarity with data warehouses - Extensive experience in gathering and documenting business requirements - Strong business acumen and data analysis skills and the ability to identify customer needs, analyze them against available solutions, and identify gaps - Interprets and presents data analysis results including explanation of statistical and financial techniques used, assumptions made and summary of results - Excellent written and verbal communication skills