Data Science Analyst

hace 5 días

Bogotá, Colombia Liberty Specialty Markets A tiempo completo

Are you curious, resilient, independent, and always interested in learning and working on state-of-the-art modeling techniques, applying the best science to deliver business value? The USDS Data Science Excellence team is looking for a Data Science Analyst to research, design, and build major modeling innovations and pioneer model sophistication across our retail insurance products. Key Responsibilities Design and build gradient-boosted decision tree models at large scale (parallel training on large datasets in EMR clusters), including problem framing, solution research, data sourcing, EDA, feature engineering, hyperparameter tuning, etc. Research new modeling techniques for structured and unstructured data, as well as processes and tools for machine learning. Own “pioneer" projects from research through proof of value and product ownership; identify and remove obstacles to deployment in partnership with infrastructure and design teams. Research, design, and assist with the implementation of models in Earnix and other platforms. Adopt a transformational mindset to improve and automate processes where applicable. Regularly engage with the data science community and participate in cross-functional working groups. About US Data Science USDS employs more than 350 full-time professionals who build advanced data science products and AI solutions for our US Retail Markets (USRM) business. By thoughtfully applying data science across USRM functions, we ensure we consistently deliver on our promises while driving sustainable growth across our portfolio. We accomplish this through a focus on model development, deployment, and decision science. In model development, we design sophisticated models that combine deep data science expertise with close collaboration across our go-to-market verticals. This integration ensures our models not only incorporate cutting-edge science but, more importantly, generate measurable business value aligned with each vertical’s strategic goals. Skills and Experience Experience building gradient-boosted decision trees and performing model interrogation. Strong coding experience; fluent in object-oriented programming, Python, and common Python data and modeling packages (LightGBM, Optuna, SHAP). Good software practices: version control (Git), pre-commits, code reviews, documentation. Experience with EDA and data preparation for building gradient-boosted decision trees. Knowledge of Earnix or similar rating tools is a plus. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. A value-driven perspective on work context and impact. Demonstrated professional-level proficiency in English, with excellent written and verbal communication skills. Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master’s degree (scientific field of study) and 1+ years of relevant experience or may be acquired through a Bachelor’s degree (scientific field of study) and 3+ years of relevant experience #J-18808-Ljbffr

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