Brand Analytics Data Analyst

Job Description

Role Overview:In this role, you will coordinate the understanding and integration of various datasets and design analytical solutions to support critical business needs, including business opportunity assessments, customer segmentation and targeting, HCP and patient opportunity identification, patient and prospective analytics, smart business experiments (test and learn), market simulations, and patient flow modeling. You will work closely with cross-functional stakeholders including Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations teams.Key Responsibilities:- Coordinate the understanding and integration of various datasets- Design analytical solutions to support critical business needs- Conduct business opportunity assessments- Perform customer segmentation and targeting- Identify HCP and patient opportunities- Analyze patient and prospective analytics- Conduct smart business experiments (test and learn)- Develop market simulations- Create patient flow modeling- Collaborate with cross-functional stakeholders from Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations teamsQualifications Required:- A bachelors degree in a quantitative field such as Engineering, Operations Research, Management Science, Economics, Statistics, Applied Mathematics, Computer Science, or Data Science is required; an advanced degree (Masters, MBA, or PhD) is preferred- At least 3 years of experience applying advanced statistical methods to large, complex datasets- Proficiency in PySpark, Python, R, and SQL is essential- Familiarity with data visualization tools such as PowerBI, MicroStrategy, Tableau, QlikView, or D3.js- Experience working on platforms like Databricks and with IQVIA datasets is highly valued- Strong Excel and PowerPoint skills- Background in statistical modeling and machine learning is a plus- Ability to extract and communicate key insights effectively- Excellent organizational and time management capabilitiesAdditional Company Details:The ideal candidate will possess strong leadership and interpersonal skills, with a proven ability to work effectively across business functions and with senior stakeholders. Excellent communication and influencing abilities are essential for presenting complex analyses in a concise and impactful manner. Strategic thinking and the ability to build credibility with the Commercial Leadership Team are key. Familiarity with scientific areas especially oncology is a plus. Experience working with big data technologies, including Spark, is desirable. Candidates should also demonstrate strong problem-solving skills and the ability to quickly grasp new concepts. Role Overview:In this role, you will coordinate the understanding and integration of various datasets and design analytical solutions to support critical business needs, including business opportunity assessments, customer segmentation and targeting, HCP and patient opportunity identification, patient and prospective analytics, smart business experiments (test and learn), market simulations, and patient flow modeling. You will work closely with cross-functional stakeholders including Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations teams.Key Responsibilities:- Coordinate the understanding and integration of various datasets- Design analytical solutions to support critical business needs- Conduct business opportunity assessments- Perform customer segmentation and targeting- Identify HCP and patient opportunities- Analyze patient and prospective analytics- Conduct smart business experiments (test and learn)- Develop market simulations- Create patient flow modeling- Collaborate with cross-functional stakeholders from Marketing, Medical, Market Access, Sales, Forecasting, and other Commercial Operations teamsQualifications Required:- A bachelors degree in a quantitative field such as Engineering, Operations Research, Management Science, Economics, Statistics, Applied Mathematics, Computer Science, or Data Science is required; an advanced degree (Masters, MBA, or PhD) is preferred- At least 3 years of experience applying advanced statistical methods to large, complex datasets- Proficiency in PySpark, Python, R, and SQL is essential- Familiarity with data visualization tools such as PowerBI, MicroStrategy, Tableau, QlikView, or D3.js- Experience working on platforms like Databricks and with IQVIA datasets is highly valued- Strong Excel and PowerPoint skills- Background in statistical modeling and machine learning is a plus- Ability to extract and communicate key insights effectively- Excellent organizational and time management capabilitiesAdditional Company Details:The ideal candidate will possess strong leadership and interpersonal skills, with a proven ability to work effectively across business functions and with senior stakeholders. Excellent communication and influencing a

Keyskills :
PythonSQLMicroStrategyTableauQlikViewExcelPowerPointStatistical ModelingMachine LearningPySparkPowerBID3jsDatabricks