Role Description As a Data Scientist at Xplore, you will play a key role in developing and deploying data-driven solutions that support business growth, customer retention, and operational efficiency. You will work on impactful projects such as churn prediction, upsell targeting, and network optimization, applying advanced analytics and machine learning techniques to solve real-world problems. This role is ideal for someone who is passionate about turning data into actionable insights, enjoys hands-on modeling, and wants to grow their expertise in a collaborative environment. - Develop and implement predictive and prescriptive models like: - Customer churn and retention strategies - Upsell and cross-sell opportunity scoring - Product coverage estimation and optimization - Perform feature engineering, model training, validation, performance tuning, and deployment using advanced ML techniques - Collaborate with cross-functional teams (marketing, sales, operations, care, product) to translate business requirements into data science solutions - Support model deployment and monitoring in production environments - Conduct exploratory data analysis and provide insights to inform business decisions - Document methodologies and ensure reproducibility of work - Stay current with emerging tools and techniques in machine learning and analytics Qualifications - 3–5+ years of experience in applied data science or machine learning - Hands-on experience with predictive modeling, time-series forecasting, and statistical analysis - Proficiency in Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) - Extensive experience with SQL and data manipulation in large datasets - Experience with cloud platforms and distributed computing - Strong problem-solving and analytical skills - Ability to communicate technical concepts to non-technical stakeholders - Familiarity with A/B testing and experimentation frameworks is a plus - Experience with end-to-end project ownership including deployment is an asset - Bachelor’s or Master’s in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) Requirements - As a condition of employment and in order to comply with industry related data security standards, this position is subject to the successful completion of a Criminal Background Check. Details will be supplied to applicants as they move through the selection process. Benefits - Xplore is committed to creating an accessible environment and will accommodate disabilities during the selection process. Please let your recruiter know during the selection process of any accommodation needs.

Role Description We are looking for a highly skilled Senior AI Data Scientist who thrives at the intersection of analytics, product thinking, and innovation. The ideal candidate will be responsible for developing Data Science & ML algorithms to solve complex, real-world business problems across the team.blue group. This role requires strong analytical skills, programming and data wrangling skills, good communication abilities and up-to-date knowledge of the latest Data Science/ML/AI developments. - Break down multi-domain business problems with a strong focus on return on investment and impact metrics, and think through the appropriate technical methods from POC to production. - Develop solutions and extract insight from data using data science and classical machine learning methods and generative AI (GenAI). - Take ownership of developing, implementing, and automating robust data science and ML models and pipelines, including feature generation, modeling, evaluation, retraining and deployment. - Translate sophisticated analytical findings and model outcomes into clear, actionable insights for stakeholders, demonstrably driving value and improvements in key business metrics. - Collaborate with cross-functional teams to understand requirements and deliver innovative Data Science/ML/AI solutions. - Conduct research on the latest Data Science/ML/AI developments and apply them to improve our systems. - Document processes, code, and findings for future reference and knowledge sharing. Qualifications - 8+ years hands-on industry experience solving data science and machine learning problems to address real-world business problems. - Expert programming skills in Python and SQL and with relevant Data Science & ML frameworks (Scikit-learn, Pandas, PyTorch, etc). - Ability to think through problems from fundamental principles. - Deep understanding of statistical and ML algorithms, methodologies and approaches, and with deep learning & LLMs. - Experience in applying statistical concepts (e.g. regressions, A/B tests, clustering, probability) to business problems. - Expertise at telling stories with data. - Strong problem-solving skills with excellent communication and documentation skills with ability to craft analysis into well-written and persuasive content. - Ability to work collaboratively with cross-functional teams. Requirements - Master's or PhD degree in Computer Science, AI, Machine Learning, or a related field (nice to have). - Software engineering background, ideally in backend or system integration (nice to have). - Deep understanding of current DataOps & MLOps practices, deploying and monitoring models and ETL (extract, transform and load) pipelines (nice to have). - Experience with AI/ML R&D (nice to have). - Experience with distributed data tools (e.g. Spark, Dask, Apache Arrow) (nice to have). Right to Work At any stage, please be prepared to provide proof of eligibility to work in the country you’re applying for. Unfortunately, we are unable to support relocation packages or sponsorship visas. Diversity & Inclusion Everyone is welcome here. Diversity & Inclusion are at our core. Far above any technical competence, we value respect, openness, and trusted collaboration. We do not tolerate intolerance. ESG At team.blue , our commitment to caring for the environment and each other is at the heart of everything we do. Our latest impact report showcases our ongoing ESG efforts and ambitious sustainability goals. Interested in learning more about our dedication to making a positive impact? Check it out here .

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.