Manager Data Analytics

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Octapharma Plasma offers professional opportunities that make a meaningful difference. We enhance the lives of patients who need our life-saving medicines. We reward the donors who provide the plasma we collect to make them. And we inspire growth and development in the teams at our donation centers, offices, and labs. We invite you to do the same in this role:

Manager, Data Analytics -Onsite (M-F)

This Is What You’ll Do:

• Highly visible enterprise leader responsible for collaboration with departments and providing direction for multiple teams to support the analytic needs of an insight-driven organization.
• Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
• Oversee and direct the development and execution of enterprise analytic solutions.
• Collaborate with business stakeholders to identify, prioritize, and develop new solution ideas, leading the implementation of chosen initiatives that integrate company strategy and best practices.
• Manage the recruitment, development, retention, and organization of the Data Analytics team in accordance with corporate budgetary objectives and human resource policies.
• Play a lead role in the migration and deployment of data pipelines via Azure Synapse / Data Bricks.
• Communicate the business value of analytics to champion analytics as a central decision-making resource.
• Promote and support a self-service architecture that enables a trusted source of distributed analytic capabilities and insights, leading the enterprise in its goal to be an insight-driven organization.
• Critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, abstract up from low-level information to a general understanding, and distinguish user requests from the underlying true needs.
• Examine, interpret, and report results of analytical initiatives to stakeholders in leadership, technology, marketing, and field operations.
• Oversee the data requests process: tracking requests submitted, prioritization, approval, etc.
• Develop and implement quality controls and departmental standards to ensure quality standards, organizational expectations, and regulatory requirements.
• Take ownership in process improvement and compliance.
• Assist in the development of governance programs to protect core data assets through the evolution of data movement (data lake/warehouse, analytic solutions, analytic delivery).
• Lead the gathering of business requirements from end users and oversee the build of technical solutions from concept to implementation.
• Facilitate meetings with multiple stakeholders, vendors, and technical staff, including building consensus and mediating compromises when necessary.
• Assist in the development of meaningful and measurable Key Performance Indicators.
• Performs other duties as assigned.

This Is Who You Are:

• A natural leader who displays strong character and integrity
• Excellent interpersonal skills, strong written and verbal communication skills
• A person committed to excellent customer service all day, every day
• Excited to teach, learn, and advance with a growing organization
• Self-motivated and willing to assume the initiative
• Attentive to every detail
• Capable of thriving while working independently

This Is What It Takes:

• Bachelor’s degree in Data Analytics, Data Science, Computer Science, Statistics, or a related field required.
• Master’s degree in Data Analytics, Data Science, Computer Science, Statistics, or a related field preferred.
• 5+ years of experience in business/data analytics, with at least 2 years in a managerial or team leadership role.
• Proven experience in designing and implementing analytics strategies that drive business growth.
• Experience with business intelligence tools such as PowerBI, Tableau, or similar.
• Expertise in SQL and other data analysis languages (Python, R, etc.).
• Experience working with large datasets in cloud platforms (AWS, Azure, GCP) and utilizing data lakes, warehouses, or data mesh architectures.
• Familiarity with predictive modeling, machine learning, and statistical methods.
• Proficien