QC Data Analyst

Overview:

The role will be responsible for providing data analytics support to enable data-driven decision making, building foundational capability to provide visibility into business processes and implementation of advanced analytics solutions to drive value.

Skills required:

• Proficiency in programming languages, with emphasis on SQL, Python, and/or R
• Experience with data visualisation tools or packages, such as Spotfire, Power BI or Tableau.
• Familiarity with common laboratory operations systems, such as LIMS and LMES an advantage.
• Experience with advanced statistical/analytical techniques and machine learning algorithms an advantage.

Key Responsibilities:

• Fostering a culture of data analytics and data visualisation through sharing of best practices and training of QC staff.
• Support the definition and advancement of a self service reporting model.
• Understanding business needs and developing practical data-driven solutions to meet those needs.
• Identify, manage and implement data analytics solutions for continuous improvement projects related to laboratory operations.
• Support to cross functional analytics projects. Building relationships with key business stakeholders, defining user requirements.
• Spotfire and Tableau reports development and maintenance.
• Development and execution of report validation protocols.
• User Acceptance Testing.
• Development activities in SharePoint and Microsoft teams.
• Liaise with IT teams for troubleshooting activities.
• Write SQL queries and provide support for routine data pull request tickets
• Performing ad hoc data mining and analysis.
• Exploring and evaluating new digital tools and techniques to advance operational capabilities.
• Predictive Model Development. Assist in the development of a wide-range of innovative data and analytics solutions, from descriptive to machine learning based. Creating analytical models and visualisations that make business and process data actionable.
• Provide support as required for design, build and validation activities related to LIMS downstream reporting application business reports.

Knowledge and Experience:

• Hold a third level qualification in data analytics, computer science or related field.
• Proficiency in programming languages, with emphasis on SQL, Python, and/or R
• Experience with data visualisation tools or packages, such as Spotfire, Power BI or Tableau.
• Familiarity with common laboratory operations systems, such as LIMS and LMES desired.
• Experience with advanced statistical/analytical techniques and machine learning algorithms an advantage.
• Excellent Organisational Skills and Time Management.
• Strong Communication Skills.
• Ability to work under minimal supervision.
• Ability to identify and manage competing priorities.