Data Analyst

Description

The Data Analyst is a core member of the Data and Innovation team, supporting both our data-driven decision-making processes and data as our asset and foundation for AI use cases. Working closely with firm leadership, the Data and Innovation team and IT, this role will enable the analysis and use of operational and corporate data sets to provide actionable insights that drive business strategies. The Data Analyst will also work with Data and Innovation team members on the exploration and prototyping of AI-driven solutions using curated datasets.

This role bridges the gap between business needs and technical capabilities by developing dashboards, reports, and queries that reflect the firm’s priorities. The ideal candidate is passionate about data, a curious and collaborative problem-solver who understands the nuances of project-based work and is committed to enhancing our data capabilities.

Requirements

• Data Documentation: Gather and analyze data from various sources to document business use, technical structure and data stakeholders. Establish documentation for internal/external data dictionaries and reporting library.

• Data Exploration and Modeling: Identify and prepare datasets for analytics and machine learning use cases, ensuring data completeness and consistency of interpretation. Develop data queries from the various applications to effectively extract key information. 

• Data Visualization and Reporting: Design and develop dashboards, reports and visualizations to support strategic and operational decision-making. Use data visualization tools like Power BI or similar to communicate data insights to stakeholders. Generate regular and ad-hoc reports to support various departments, including marketing, finance, and operations. Provide insights and recommendations based on data analysis.

• Performance Analytics and Decision Support: Perform ad hoc and recurring data analysis to support project performance, business development, and operational efficiency. Identify trends, patterns, and anomalies in data to inform decision-making. Support the development of KPIs and performance metrics aligned with firm objectives. Identify improvement opportunities and provide data-driven insights to support operational and strategic decisions.

• Stakeholder Engagement: Work with firm leadership, project teams and departments to understand their data needs and provide solutions. Collaborate with IT and business stakeholders to promote data literacy, elevate organizational data fluency and establish and support the enterprise data model across systems and tools.

• Data Quality: Support the development of data quality processes owned by business stakeholders to ensure data accuracy and consistency across business systems and reporting tools.

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Preferred Qualifications & Skills:

• Education and Experience: Bachelor’s degree in Data Science, Information Systems, Informatics, or a related field. 2–4+ years of experience in a data analysis or similar role. Experience with data visualization tools and statistical software is required.

• Technical Skills: High proficiency with Excel models and data visualization tools (e.g., Power BI, Tableau). Proficiency in SQL or similar tools languages for data exploration and analysis (VBA & SQL). Experience with database management systems (e.g., SQL Server, MySQL). Experience with project-based ERP systems (e.g. Deltek Vantagepoint), data warehouses and data lakes are a plus.

• Analytical Skills: Strong analytical and problem-solving skills. Ability to interpret complex data sets and provide actionable insights.

• Communication Skills: Excellent verbal and written communication skills. Ability to present data findings to non-technical stakeholders in a clear and concise manner.

• Collaboration Skills:  Collaborates well with multiple functional teams and projects in a matrixed environment. Comfortable navigating dual reporting lines and managing competing priorities.

• Attention to Detail: High level of accuracy and attention to detail. Ability to manage multiple tasks and meet deadlines.

• Innovation Mindset: Demonstrated passion for data and technology. Participation in data-related projects, research, or industry forums is a plus. Proven ability to experiment, iterate, and implement new ideas in a real-world context.

• Experience in Data Models and Reporting Packages: Familiarity with data models and reporting packages to analyze datasets and provide insights.