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Profile Summary
Result oriented model developer with extensive experience in developing data models using Excel and VBA, complemented by a strong background in data analytics specific to pharmaceutical industry. Possesses a unique blend of technical skills and analytical expertise to create insightful models that drive effective business decision making. Adept at translating complex datasets into actionable insights while ensuring compliance with industry methodologies and regulatory requirements.
Key qualifications:
Analytical skills and insights generation:
- Strong analytical skills with a proven track record in working with large datasets to drive meaningful insights and predictions.
- Experience in applying statistical methods to analyse trends and patterns in data, supporting decision making with quantitative evidence.
Model development expertise:
- Extensive experience in developing sophisticated models using Excel VBA and python, optimizing processes for data analysis and reporting.
- Proven ability to design and implement complex excel spreadsheets that incorporate advanced formulas, macros and automation features to streamline data manipulation and visualization.
Familiarity with power apps:
- Knowledge in using power apps to build custom applications that
- enhance data interactivity, enabling users to access and interaction with data models easily.
- Ability to integrate power apps with excel based models to improve user experience data accessibility.
Pharma industry knowledge:
- Solid understanding of pharmaceutical industry, including regulatory framework, clinical trial methodologies and various data types such as HER, laboratory data, and patient reported outcomes.
- Capability to develop models that adhere to industry standards and regulatory requirements, ensuring that data is handled with accuracy and compliance.
Data Analysis and SQL proficiency:
- Proven experience in data analysis and manipulation using SQL, with the ability to write complex queries for data extraction, transformation and loading (TL) purposes.
- Skilled in performing data cleansing and preparation for modelling, ensuring data accuracy and integrity.
Technical skills:
- Modelling tools: Excel, VBA
- Data analysis: sql, excel(advance functions, pivot tables)
- Statistical techniques, descriptive statistics, trend analysis, predictive modelling
- Data sources: familiarity with various pharmaceutical data sources including clinical trial database and laboratory information systems.
EY | Building a better working world
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