Sr Data Scientist developing and implementing machine learning models for QVC Group's data-driven solutions. Focused on enhancing business decisions, customer experience, and operational efficiency.
Responsibilities
Hands-on design and development of machine learning and AI models, and successfully implement with end-users from start to end; models must be validated to highest standards of accuracy, consistency, and business relevance
Independently manage project priorities and deliverable timelines, keeping leadership and stakeholders aligned on progress
Proactively troubleshoot and resolve obstacles to ensure on-time delivery, collaborating directly with Business and IT partners to address complex dependencies
Be on the cutting edge of implementing and activating GenAI and Agentic AI technologies with potential tool-chaining of ML models to simplify complex workflows and analyses, enhance decision-making, and transform business planning and execution processes
Present project updates and perform demonstration of successfully implemented Data Science capabilities to the Executive leadership audience
Cultivate technical excellence by mentoring analytics/data science team members on data science best practices and identifying opportunities to automate workflows
Requirements
8+ years of overall analytics experience, can be inclusive of post graduate work
Education: Bachelors in Data Analytics, Economics, Operations Research, Engineering, Computer Science, Statistics, Mathematics, Econometrics or similarly related analytical field; Masters in Lieu of 1 year of experience; PhD in Lieu of 3 years of experience
6+ years of experience with Data Science model development with a combination of Bayesian statistics, multivariate regression analysis (beyond linear regression), forecasting/predictive analytics, supervised learning, unsupervised learning, time-series analysis, mixed integer and linear programming using optimization packages such as Gurobi, CPlex, or others
Mastery in one or more Data Science platforms: Databricks, Microsoft Azure, Google BigQuery or AWS cloud platforms, and practical machine learning using frameworks such as scikit-learn, H2O, TensorFlow, Mllib, finetuning LLMs, Multi-Agent Systems
Excellent Problem-Solving ability to independently breakdown complex business problems and apply Data Science tools and models to solve problems, validate outputs, and influence results.
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