Analyse variances in financial metrics, identifying root causes and potential risks. Business Partnering with Finance & other areas of the business (FRA, Marketing, Sales, Trade and other functions) to support impactful information gathering to independently identify and analyze various aspects of the business.
Drive/enable innovative ideas and use of digital tools to improve processes and understand performance by following the principles of automation, simplification, and standardization
Build automated solutions to monitor and flag data anomalies in real-time, ensuring data quality and integrity.
Design and implement machine learning models and advanced algorithms to identify patterns, detect anomalies, and forecast trends in financial data.
Partner with stakeholders to define requirements and ensure solutions align with business needs.
Demonstrate expertise in data storytelling, presenting findings in clear, concise, and actionable ways to non-technical stakeholders.
Contributing to team and departmental success by performing requested tasks as needed.
Qualifications
Advanced proficiency in Python and/or R for data analysis, anomaly detection, and pattern recognition.
Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch).
Strong SQL skills for data querying and optimization.
Familiarity with ETL tools like Alteryx or DataIku.
Knowledge of U.S. healthcare finance systems (preferred but not mandatory)
Bachelor’s/Master’s in technology, Data Science, or related field; MBA (Finance) preferred.
5-9 years of relevant experience in insights & analytics, data science and machine learning.
