Plasma Senior Data Analyst / Data Scientist

• Collects and analyzes current and historical data to identify strategic and operational trends and insights. Identifies threats and opportunities for continuous improvement that will positively impact business results (e.g., cost per gram, process improvements, quality improvements, site selection, etc.)
• Provides data support to ensure accuracy in calculations and realization of financial benefit from improvement initiatives
• Extracts, queries, and analyzes large, complex datasets from multiple enterprise systems using SQL and Python
• Develops actionable insights by identifying trends, patterns, risks, and opportunities that support strategic and operational decision-making
• Designs, develops, and maintains dashboards, reports, and KPIs that enable leadership to monitor business performance
• Synthesizes analytical findings into clear business recommendations and senior leadership[1]level presentations
• Builds statistical models, forecasting models, and automated analytical solutions that improve reporting efficiency and business decision making
• Collaborates with process teams to elicit and understand requirements, challenges, and develops analytical insights from data to support data-driven solutions and improvements
• Performs ad hoc analyses to support strategic initiatives, operational improvements, and senior leader requests
• Ensures data quality by validating datasets, identifying anomalies, and partnering with data engineering/science teams to resolve data issues
• Develops scalable analytical processes and reusable code to improve automation and reduce manual reporting efforts
• Partners with cross-functional teams including Operations, Quality, Data Science, I&T, Finance, and Business Intelligence to deliver enterprise analytics solutions

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Business Analytics, Engineering, or related field.
• 5+ years of experience as a Senior Data Analyst, Business Intelligence Analyst, or Analytics professional
• 2-4 years of experience applying Data Science methodologies including predictive modeling, statistical analysis, or machine learning
• Familiarity with A/B testing, statistical experimentation, and advanced analytical methodologies
• Advanced SQL experience with the ability to write complex queries against large relational databases
• Strong Python experience for data analysis, automation, statistical analysis, and model development
• Experience working with large enterprise datasets and multiple structured data sources
• Demonstrated experience translating analytical findings into actionable business recommendations
• Experience developing dashboards and KPI reporting using Power BI, QlikSense, Tableau, or similar visualization tools * Excellent analytical, problem-solving, and communication skills
• Self-starter, motivated, independent, and team player who works well under pressure
• Ability to manage multiple priorities and multiple projects simultaneously

Preferred/Nice to Have:

• Master’s degree in Data Science, Analytics, Statistics, Computer Science, or related discipline
• Experience within healthcare, biotechnology, pharmaceuticals, manufacturing, or plasma operations
• Experience with cloud-based data platforms (Snowflake, Azure, AWS, and Google Cloud)
• Knowledge of predictive analytics, forecasting, and optimization techniques
• Experience automating recurring reporting and analytical workflows
• Experience supporting executive leadership with strategic analytics and business insights

Technical Skills:

• SQL (advanced querying, joins, CTEs, window functions, stored procedures)
• Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
• Power BI, Tableau, QlikSense, SAP
• SQL Server, Snowflake, Oracle, ServiceNow, Jira
• Statistical analysis, predictive modeling, forecasting, regression analysis
• Data visualization, dashboard development, KPI reporting
• Microsoft Excel (advanced), PowerPoint, Minitab (nice to have)
• Git, Jupyter Notebook, ETL concepts, data validation, and automation.