Job Description
Role Title: Data Analyst
Reports To: Project Manager/Database Lead
Direct Reports: None
Indirect Reports: None
Role Purpose:
The Data Analyst interprets data to produce actionable insights, such as reports, dashboards, and interactive visualizations, to enhance business decision-making and drive improvements.
Key Responsibilities:
Technical Management: Oversee the technical scope of projects, ensuring alignment with requirements throughout all stages.
Data Gathering & Interpretation: Collect data from various sources (data warehouses, databases, data integration) and identify patterns and trends.
Record Management: Develop and maintain record management processes and policies.
Client Relationships: Build and sustain relationships at all levels within the client base to understand their needs and requirements.
Data Insights & Reporting: Provide sales data, proposals, insights, and account reviews to clients.
Process Optimization: Identify and implement efficiencies and automation opportunities within processes.
Automated Data Processes: Set up and maintain automated data processes.
External Tools: Evaluate and integrate external services and tools for data validation and cleansing.
Performance Tracking: Produce and track key performance indicators (KPIs).
Data Analysis: Analyze data sets to provide relevant information, design and conduct surveys, and prepare reports for internal and external audiences.
Visualization & Benchmarking: Create dashboards, graphs, and visualizations to showcase business performance and provide sector and competitor benchmarking.
Predictive Modeling: Develop predictive models and share insights with clients as needed.
Stakeholder Interaction:
Internal Stakeholders: Project Manager/Database Lead – Regular reporting and updates.
External Stakeholders: Clients – Engagement, reviews, and feedback.
Competencies Required:
Functional Competencies/Skills:
Leveraging Technology: Expertise in current and emerging technologies (automation, tools, systems) to drive efficiencies and effectiveness.
Process Excellence: Ability to adhere to standards and norms for consistent results, effective control, and risk reduction.
Technical Knowledge: Proficiency in programming languages and software (Python, Microsoft Excel, VBA, Matlab, SQL) and data analytics tools.
Competency Levels:
Foundation: Basic understanding and partial demonstration with minimal support.
Competent: Consistent performance in various situations without guidance.
Expert: Mastery of competency, applicable in all situations, and guiding others.
Master: Coaches others, builds organizational capability, and is a recognized resource within the organization.
Behavioral Competencies:
Formulation & Prioritization
Client Centricity
Execution Excellence
Passion for Results
Confidence
Business Acumen
Performance Metrics:
Data Analysis & Reporting:
Number of automations implemented
On-time delivery of reports
Customer Satisfaction (CSAT) score
Zero customer escalations
Data accuracy and quality
