Job Description:

EY is seeking an experienced Senior Statistical Modeler to join their GDS AI & Data team. In this role, you will help clients leverage data and technology to solve complex business problems, particularly in sectors like Banking, Insurance, Healthcare, Manufacturing, Retail, Auto, Supply Chain, and Finance.

You will work on extracting insights from data, building statistical forecasting models, and providing actionable recommendations. This is an opportunity to work in a collaborative, interdisciplinary environment with a strong emphasis on learning, coaching, and personal development.

Key Responsibilities:

• Develop statistical forecast models for the pharma industry with deep understanding of patient flows and treatment journeys across oncology and non-oncology therapies.
• Apply machine learning techniques, including supervised and unsupervised learning, model evaluation, and performance metrics like ROC curves.
• Manipulate and analyze data using Python, R, SQL, and Excel.
• Build and maintain data visualization dashboards using Matplotlib, Seaborn, ggplot2, or similar tools.
• Collaborate with teams to provide data-driven insights and actionable recommendations for business challenges.
• Continuously update skills, learn new methodologies, and share knowledge with team members.

Key Technical Skills:

Python, R, Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret, SQL, Excel, Matplotlib, Seaborn, ggplot2, Supervised Learning, Unsupervised Learning, Model Evaluation, Statistical Forecasting, Pharma Analytics

Requirements:

• 5–7 years of experience in building statistical forecast models, preferably in the pharma industry.
• Strong understanding of patient flows and treatment journeys in oncology and non-oncology therapies.
• Hands-on experience with Python and R, including relevant libraries for statistical modeling.
• Proficiency in data manipulation and visualization tools.
• Ability to work in a fast-paced environment with commercial acumen and technical expertise.
• Excellent teamwork, communication, and problem-solving skills.

Preferred:

• Previous experience in cross-functional teams within analytics or data science projects.
• Knowledge of advanced machine learning techniques and model evaluation.
• Familiarity with healthcare data, pharma industry workflows, or similar domains.