
Senior Data Analyst
3 days ago
The Senior Data Analyst is a hands-on role responsible for developing and maintaining user-centric reporting and providing subject matter expertise to business leaders in alignment with business strategy and organizational needs. This role involves curating, monitoring, tracking, and notifying on data and insights across the enterprise. The Senior Data Analyst will identify business metrics and reporting solutions to enhance the business intelligence function.
The Senior Data Analyst will respond to key business opportunities and problems using data to investigate and generate solutions. They will proactively monitor portfolio performance, investigating positive and negative trends to understand current and future implications. The role also involves consulting and supporting stakeholders across the organization with the creation of analysis that informs strategic initiatives and considers a business mindset. Acting as the technical business owner on projects, the Senior Data Analyst ensures that technical solutions meet business requirements as defined by key stakeholders.
What will you do?
- Respond to key business opportunities and problems using data to investigate and generate data driven solutions such as dashboards and data assets.
- Produce analysis that will support decision making at a higher level. This analysis often results from unfolding business opportunities and issues and helps to infer the overall direction of business performance.
- Design and prototype new analyses, reports, visualizations, and data analytics in accordance with data governance and reporting design standards.
- Identify business metrics and reporting solutions that will improve the overall effectiveness and efficiency of the Business Intelligence function.
- Make sense of large amounts of disparate data to tell a consistent story focused on key strategic decision-making for executives and management.
- Proactively monitor performance of portfolio and investigate positive and negative trends to understand current and future implications.
- Data storytelling: Crafting a narrative around data to make insights more engaging and understandable.
- Data monitoring: Continuously tracking data to ensure accuracy and identify trends or anomalies.
- Data reconciliation: Ensuring consistency and accuracy by comparing and aligning data from different sources.
- Creation of reporting solution in Power BI: Developing interactive and visually appealing reports using Power BI to facilitate data-driven decision-making.
- Creation of data asset using SQL or Python that is used in consumption of downstream analysis (OBT creation).
- Consult and support stakeholders across the organization with creation of analysis that informs strategic initiatives.
- Data storytelling: Crafting a narrative around data to make insights more engaging and understandable.
- Business contextualization of technical output: Translating technical data into business-relevant insights to inform strategic decisions.
- Data reconciliation: Ensuring consistency and accuracy by comparing and aligning data from different sources.
- Benefits Realization Quantification: Measuring the tangible and intangible benefits achieved from a project or initiative.
- Tracking of Targets and overall corporate performance: Monitoring key performance indicators (KPIs) to assess progress towards goals and overall business health.
- Act as the technical business owner on projects, ensuring that technical solutions meet business requirements as defined by stakeholders.
- Data modelling: Designing the structure of data solution to organize and manage data efficiently.
- Requirements gathering: Collecting and documenting the needs and expectations of stakeholders for a project.
- Data reconciliation: Ensuring consistency and accuracy by comparing and aligning data from different sources.
- Creation of reporting solution in Power BI: Developing interactive and visually appealing reports using Power BI to facilitate data-driven decision-making.
- Creation of data asset that is used in consumption of downstream analysis (OBT creation): Building a data resource that supports further analysis and reporting activities.
What will you need to succeed in this role?
- Bachelor's or master's degree in Mathematics, Statistics or a related field.
- Knowledge of data assets and key attributes and metrics commonly used in Business Intelligence, particularly within the P&C insurance sector.
- Experience working with enterprise-level data and reporting, including best practices for handling large quantities of data.
- Proven analytical ability to synthesize data, identify trends, and produce actionable insights.
- Knowledge of SQL databases, Business Intelligence, and analytics tools (Python, R, or equivalent).
- Ability to generate and engineer data features for advanced analytics and reporting.
- Ability to identify new opportunities for data acquisition and assist in the integration and utilization of new data assets.
- Strong communication skills to explain complex problems and solutions to an executive-level audience.
- Ability to collaborate with internal clients, such as Data Scientists and Business Users.
- Ability to multi-task, prioritize work, manage expectations, and meet deadlines in a fast-paced environment.
- Ability to work with minimal supervision while maintaining focus and productivity.
- Adaptability to new situations, changing business needs, and ambiguity.
- Curiosity and continuous learning to enhance knowledge and grow within the insights team.
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