Data Analyst

Responsibilities:

• Efficiently mine, clean, manipulate, and analyze very large volumes of multifaceted data, using various data analysis techniques.
• Perform exploratory data analysis that results in meaningful insights and recommendations to the business.
• Proactively identify and surface opportunities that improve efficiency, revenue generation, and cost cutting
• Collaborate with key stakeholders to define metrics and KPIs that measure effectiveness of operations and support decision-making.
• Effectively communicate analytical findings to business partners in the form of dashboards and other visuals.
• Develop predictive data models that help determine the result of future business decisions.
• Design reports, dashboards, and scorecards that visualize company performance.
• Maintain detailed data dictionaries and documentation for all analysis processes and solutions.
• Translate business needs into technical requirements for reporting and necessary data extracts.

Qualifications:

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
• Bachelor's degree in Business Analytics, Mathematics, Statistics, Economics, Computer Science or another analytically challenging field required.
• Three (3) years of professional experience in an analytical role, solving business problems through statistical analysis and strategic planning required.
• Adept at writing complex and optimized T-SQL queries against very large datasets.
• Proficient in Python for data acquisition & cleaning of large datasets, diagnostic analytics, and predictive modeling.
• Strong statistical analysis and problem-solving skills, with excellent attention to detail.
• Proficient with Jupyter Notebooks, Power BI, and other visualization tools to present analytical findings.
• Proficiency with Excel in a reporting and dashboarding capacity.
• Experience with APIs, web scraping, and machine learning a strong plus.
• Ability to work independently and as part of a team, manage time effectively, and meet project deadlines.

Key Skills:

• Data cleaning and preparation.
• Data analysis and exploration.
• Statistical knowledge.
• Creating data visualizations.
• Creating dashboards and reports.
• Writing and communication.
• Domain knowledge.
• Problem solving.