Senior Data Analyst

Rocket Companies•Detroit, MI

About The Position

The Senior Data Analyst collects, organizes, and analyzes data from various sources to turn findings into context and recommendations. The role uses data analysis techniques and statistics to illustrate business performance, and integrates, transforms, and improves large volumes of data at the project or company level to streamline processes, improve efficiency, and support informed decision-making. The analyst demonstrates leadership among peers and deep knowledge of the relevant industry and business. The role proactively identifies and communicates business opportunities and recommendations through data manipulation, programming, statistics, and visualization. It uses data to support or challenge business solutions with executive leadership and other stakeholders, leads the design and validation of all phases of research projects, presents results, and guides iterative improvement. The analyst maintains stakeholder relationships and alignment, defines and validates project data requirements, evaluates data quality and organizational data sources, and creates and supports business intelligence tools, databases, dashboards, reports, and methods. Additional work includes documenting technical design standards for reporting solutions, conducting exploratory data analysis, monitoring the competitive environment using relevant external data, staying informed about pertinent industry and business trends, and mentoring teammates.

Requirements

Bachelor’s degree or equivalent experience in a scientific discipline, mathematics, applied statistics, information technology, or a related field.
4 years of experience or equivalent competency identifying business problems, conducting data experiments, performing statistical analysis, and synthesizing findings to guide business decisions.
Experience leading end-to-end data analysis projects that resulted in positive business changes.
Expertise creating data visualizations using modern business intelligence tools to highlight relevant insights.
Proficiency with industry-standard statistical analysis tools such as SAS, R, or Python.
Experience training and mentoring peers.
Experience creating data sets with advanced SQL or other querying languages and using them to develop business strategies.
Experience researching data lineage.
Advanced practical knowledge of standard statistical measures, probability theory, and qualitative and quantitative techniques.
Experience working with data warehouses.
Experience with data mining or other exploratory techniques.
Experience working with structured and unstructured data.
Experience writing software functions to support data analysis.
Experience contributing to standards and processes that increase efficiency and impact.
Conceptual knowledge of logical and physical data models.
Domain knowledge of multiple business areas.

Nice To Haves

Comprehensive knowledge of at least one business area and its data, including industry or other external sources.
Experience in several business areas and familiarity with associated data.
Conceptual knowledge of big data, machine learning, or data science.

Responsibilities

Identify and communicate business opportunities and recommendations using data manipulation, programming, statistics, and data visualization.
Use data to support and challenge business solutions with executive leadership and other stakeholders.
Lead the design and validation of all phases of research projects, present results, and guide iterative improvement.
Maintain stakeholder relationships and alignment to meet objectives.
Define, gather, and validate project data requirements and evaluate data quality.
Evaluate the quality of organizational data sources.
Create and support business intelligence tools, databases, dashboards, reports, or methods.
Document technical design standards for reporting solutions to ensure accurate development.
Identify, document, and use exploratory data analysis to investigate assumptions.
Identify and analyze relevant external data to monitor the competitive environment.
Stay informed about industry or business trends that pertain to data.
Mentor teammates on these responsibilities.