Lead Data Scientist building GenAI - driven products and ML solutions for S&P Global. Mentoring team members and delivering high - impact projects in a global environment.
About the role
- 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.
Benefits
- competitive compensation
- paid time off
- an employee assistance program
- parental leave
- paid volunteer hours
- amazing company discounts
- health care benefits starting on day 1
- 401(k)
- tuition reimbursement benefits
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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