Data Science Leader for Finance Innovation
6 days ago
About the Role:
Drive impactful financial outcomes through data-driven decision-making at the LEGO Group. As our Advanced Analytics Lead, you will lead advanced analytics across the Finance Organization, integrating insights into strategic decisions.
Key Responsibilities:
Identify and address complex financial challenges by developing advanced analytics models and collaborating with finance partners to provide innovative, data-driven solutions.
Develop and implement advanced analytics models using machine learning techniques, deploying AI/ML models into production while integrating them with existing data and IT systems.
Support strategic decision-making by applying statistical models and techniques to understand financial phenomena and predict future trends.
Collaborate with various groups to enhance the value of AI, ML, and other data science initiatives, working with citizen data scientists, data engineers, and domain experts across the organization.
Our Team:
You will join the Corporate Finance, Systems, Analytics, and Insights team, responsible for the accuracy and quality of all data across the Finance organization, driving our agenda to be more digital and data-driven.
Your Skills and Qualifications:
A strong understanding of statistical and mathematical concepts, including linear algebra, probability theory, and algorithms.
Technical skills in programming languages such as Python, experience with data manipulation libraries like Pandas and NumPy, and familiarity with data visualization tools like Matplotlib and Seaborn.
Expertise in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) and an understanding of MLOps practices, including DevOps principles like IaC and CI/CD pipelines.
Experience with big data technologies (e.g., Spark) and cloud platforms (e.g., AWS, Google Cloud, Databricks), as well as proficiency in DSML platforms like Amazon SageMaker or Azure ML.
Advanced analytical skills, including the ability to build and run advanced analytics models, interpret complex data, and deliver actionable insights.
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