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Summary
The Senior Financial Data Analyst, working in collaboration with and in support of the firm’s strategic initiatives, in the Data Analytics group is responsible for data-driven forecasting, leading analytics projects, advancing the firm’s data innovation efforts, and applying advanced analytical techniques to support strategic decision-making. This role requires strong analytical and technical skills, financial acumen, and a passion for leveraging data to drive business outcomes.
The Sr Financial Data Analyst uses tools such as Power Desktop/Power BI Report Builder (SSRS) to deliver high-impact analytics, reporting, and dashboards; develop complex data models; and identify and resolve data quality issues. This individual leads large-scale analytical initiatives, mentors’ junior analysts, and collaborates with stakeholders to prioritize business needs and deliver actionable insights.
Key skills include proficiency in programming/query languages, data analysis, and strong presentation skills. The role also involves fostering collaboration, driving continuous improvement, contributing to the firm’s data strategy, and ensuring timely, accurate deliverables. Working closely with functional leads across the firm, this position conducts research, analyzes and presents data to identify trends, forecast outcomes, and support informed decision-making related to financial performance. Duties will include financial performance data analysis and presentation, interpreting data from analysis using statistical techniques, reporting, forecasting, developing and implementing data collection techniques to optimize statistical efficiency.
Location
This position can sit in our New York, Chicago, Reston, or Short Hills office and offers a hybrid work schedule.
Responsibilities
Utilize Power BI and other advanced analytics tools to deliver comprehensive and high-impact analytics, forecasting, reporting and insight-driven solutions.
Collaborate with FP&A, Service Delivery, Senior Finance leadership and other key stakeholders to identify and prioritize complex business problems.
Implement best practices and innovative solutions to enhance data integrity.
Drive and manage large-scale analytical projects that span multiple teams and functions.
Coordinate cross-functional efforts to ensure project alignment with business objectives and successful execution.
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