Data analyst
Resume examples

Assess key parameters using SQL and Python to drive product development with insightful analysis and collaboration. Maintain dashboards and data warehouses to quickly deliver information. Evaluate existing practices for efficacy and accuracy.

• Optimize existing Tableau SQL queries to process data for new product launches.
• Increase product sales 12% via market and exploratory analyses.
• Improve SPSS syntax execution by debugging outdated code and writing Python scripts to automate processes for integration with other applications.

Tasked with transferring data into new formats to make the information more appropriate for analysis. Built analytical tools to automate the data collection process and decrease the amount of time for reporting and suggesting technological advancements and/or changes.

• Created and improved computer software and hardware under the direct supervision of the lead data scientist and computer engineers.
• Helped develop streamlined algorithms to reduce the amount of processing time and make computer tasks more efficient.
• Tested scalable schema designs, relational database, query performance, workflow optimization, and documentation.
• Developed significant and concise analytic objectives according to business goals and initiatives and under the guidance of department supervisors.
• Designed and built interactive dashboards, machine learning models, and innovative analytics tools using a variety of programming languages.

Automated data ingestion procedures and improved overall reporting efficiency by 40% with the introduction of custom-built data views and reports. Collaborated with stakeholders and supervisor to define requirements and deliver tailored solution.

• Met with supervisor to outline process improvement strategy.
• Collaborated with engineering colleagues to develop and test algorithms designed to replace manual data ingestion, storage, and assessment operations.
• Liaised with stakeholders to provide updates and integrate feedback as needed.
• Obtained leadership approval and facilitated integration of new program utilizing SQL database and Google Analytics API technology.

Collaborated with three junior data analysts to process usable information and reported findings to appropriate managers and decision-makers. Helped to establish KPIs to evaluate the effectiveness of the company’s financial decisions, requiring the analysis of large data sets to find relevant information.

• Analyzed large and complex data sets to detect potential issues that could lessen productivity and provided deliverable actionable insights.
• Assisted in the development, design, and maintenance of four products of business at the company.
• Worked with product managers and engineers to translate the analysis into meaningful impact for the business.
• Identified actionable insights and made recommendations to project managers and cross-functional groups as directed by the supervisor.
• Supported payment risk control team by aggregating data from various sources to construct seamless information pipelines.

Searched through large data sets for useful information to assist in the business decision-making process as directed by the lead data analyst and other key stakeholders. Demonstrated persistence, statistical, and engineering capabilities necessary in understanding biases and inconsistencies in data.

• Tasked to establish methodologies to improve algorithms to allow advancements in machine learning and cloud computing systems.
• Helped design new computer architectures to improve performance, effectiveness, and efficiency in computer software and hardware.
• Executed and troubleshot analysis workflow while maintaining excellent and comprehensive written records of activities.
• Collaborated effectively between the business department and data groups, by paying meticulous attention to detail and differentiating communication and presentation skills.
• Performed data exploration to understand end-user behavior and identify opportunities for improving software features.