Group Analyst Assistant | Data Analysis & Business Intelligence

🎯 Role Definition

As a Group Analyst Assistant, you are the backbone of our analytics function. Your primary mission is to empower our senior analysts and leadership by providing them with timely, accurate, and actionable data insights. You will be deeply involved in the entire data lifecycle, from gathering and cleaning raw data to creating compelling reports and preliminary analyses. This role is a fantastic opportunity for an aspiring analyst to develop foundational skills in data management, business intelligence, and financial modeling while making a tangible impact on the organization's performance and strategic direction. You will be a key contributor to a culture of data-driven excellence.

📈 Career Progression

Typical Career Path

Entry Point From:

Recent Graduate (Quantitative Fields)
Data Entry Specialist / Coordinator
Junior Business or Financial Analyst Intern

Advancement To:

Group Analyst / Senior Analyst
Business Intelligence Developer
Data Analyst / Data Scientist

Lateral Moves:

Project Coordinator
Marketing Analyst
Financial Planning & Analysis (FP&A) Analyst

Core Responsibilities

Primary Functions

Assist senior analysts in gathering, cleaning, and validating large, complex datasets from multiple sources (e.g., SQL databases, ERP systems, third-party APIs) to ensure data integrity.
Develop, maintain, and automate recurring reports, dashboards, and performance scorecards using Excel, Power BI, and Tableau to track key performance indicators (KPIs).
Conduct preliminary quantitative and qualitative analysis on market trends, customer behavior, and operational performance to identify initial insights and anomalies for further investigation.
Prepare comprehensive presentations, charts, and data visualizations that effectively communicate analytical findings and recommendations to internal stakeholders and management.
Support the development and maintenance of financial models for forecasting, budgeting, and variance analysis under the guidance of senior team members.
Perform detailed data reconciliation to ensure consistency and accuracy between different systems and reports, troubleshooting discrepancies as they arise.
Respond to data inquiries from various business units, providing prompt and accurate information to support their operational needs.
Monitor and analyze key business metrics, highlighting trends, patterns, and potential risks or opportunities to the analytics team.
Create and maintain detailed documentation for data sources, analytical methodologies, and reporting processes to build a robust knowledge base.
Collaborate with the IT and data engineering teams to help define data requirements for new reports and system enhancements.
Support the quarterly and annual business planning and review cycles by compiling historical data and preparing foundational analysis.
Conduct ad-hoc research and analysis on specific business questions or challenges as directed by senior analysts or leadership.
Assist in the preparation of materials for executive-level meetings, ensuring all data presented is accurate, vetted, and clearly articulated.
Manage and organize the team's shared data resources, file repositories, and analytical tools to ensure efficiency and ease of access.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis to uncover hidden patterns and insights.
Contribute to the organization's data governance initiatives by helping to define and enforce data quality standards.
Collaborate with business units to translate their data needs and questions into actionable technical and engineering requirements.
Participate in sprint planning, daily stand-ups, and other agile ceremonies as a member of the broader data and analytics team.
Monitor industry news, competitor activities, and macroeconomic trends to provide valuable context for internal analysis and strategic planning.
Assist in user acceptance testing (UAT) for new data tools, reporting platforms, and system upgrades to ensure they meet business requirements.
Proactively identify opportunities for process improvement within the analytics workflow, suggesting ways to enhance efficiency, accuracy, and automation.
Participate in training sessions and workshops to continuously develop technical skills and knowledge of industry best practices.

Required Skills & Competencies

Hard Skills (Technical)

Advanced Microsoft Excel Proficiency: Expertise in PivotTables, VLOOKUP, INDEX/MATCH, complex formulas, and experience with Power Query and macros is essential.
Database Querying: Strong practical knowledge of SQL for writing queries to extract, manipulate, and aggregate data from relational databases (e.g., SQL Server, PostgreSQL).
Data Visualization Tools: Hands-on experience with at least one major BI platform such as Power BI, Tableau, or Qlik for creating interactive dashboards and reports.
Data Analysis Fundamentals: Solid understanding of basic statistical concepts and analytical techniques to interpret data effectively.
Presentation Skills: Proficiency in Microsoft PowerPoint or Google Slides to build clear, concise, and visually appealing presentations that tell a story with data.
Python or R (Preferred): Familiarity with a scripting language for data analysis, particularly with libraries like Pandas, NumPy, or dplyr, is a significant advantage.

Soft Skills

Exceptional Attention to Detail: A meticulous and precise approach to handling data and analysis, ensuring the highest level of accuracy.
Strong Analytical & Problem-Solving Mindset: The ability to break down complex problems, identify root causes, and propose logical solutions.
Clear & Concise Communication: Excellent written and verbal communication skills, capable of explaining technical concepts to non-technical audiences.
Proactive & Eager to Learn: A self-starter mentality with a strong curiosity and a demonstrated desire to learn new tools, techniques, and business domains.
Time Management & Organization: Proven ability to manage multiple tasks, prioritize effectively, and meet deadlines in a fast-paced environment.
Collaborative Team Player: A positive attitude and strong interpersonal skills to work effectively within the analytics team and across different departments.

Education & Experience

Educational Background

Minimum Education:

Bachelor's Degree from an accredited university or college.

Preferred Education:

Bachelor’s or Master's Degree in a quantitative or business-related field.

Relevant Fields of Study:

Finance, Economics, Statistics
Business Administration, Computer Science, Mathematics

Experience Requirements

Typical Experience Range:

1-3 years of relevant experience in a data-focused role, including applicable internships or co-op positions in analytics, finance, or business intelligence.

Preferred:

Prior experience working within the financial services, insurance, consulting, or retail industries is highly desirable.
Demonstrable experience through a portfolio of projects (e.g., on GitHub) or academic work that showcases analytical and technical skills.