Roles & Responsibilities:
The Data Analyst will lead and perform complex analysis in an evolving data environment for Pharmaceutical Manufacturing and engineering Division. In addition to very strong technical skills, this position requires superb business process analysis and interpersonal skills. The ability to extract and analyse impact of the annotated data to train the deep learning algorithm. To spot out the patterns, and related trends is needed, with the subsequent ability to synthesize the data into understandable metrics for non-technical users that be used for day to day decision making.
- Identify the opportunities in Pharma Manufacturing Engineering Division for Data based decision making and workflow improvements
- Complete projects that require Data Mining, Analysis, and Presentation.
- Focus on Solutions, Dive into Projects, quickly identify Drivers in Data.
- Identify relevant Trends, conduct follow-up Analysis & prepare Visualizations.
- Develop Dashboards to track remediation of issues.
- While the focus of this role is the extraction and interpretation of data, it also requires the capacity to identify, explore, interpret and present key trends, ideas and concepts.
Requirements:
- A Bachelor’s degree in Math, Computer Science, Business Analytics, or a related field is required. Candidates with a Masters’ degree will be preferred.
- 4 years’ Working Experience with tools like Power BI (essential), Tableau, and Excel, SharePoint Workflow Development, Power Apps and 2 years of experience with Pharma industry.
- Proficiency in SQL and Database management.
- Effective Communication and Project Management skills are important.
- The ideal candidates should have experience working in a business/data analysis role in the Pharma or related manufacturing business processes.
- Strong Mathematical & Statistical Skills.
- Self-starter – must be productive with minimal direction.
- Ability to work in a fast-paced, technical, cross-functional environment.
- Excellent visual design sense regarding clear and accurate presentation of data
