Data Analyst

At StraightLine, we’re proud to stand at the forefront of the Big Data revolution. Using the latest analytics tools and processes, we’re able to maximize our offerings and deliver unparalleled service and support. To help carry us even further, we’re searching for an experienced data analyst to join our team. The ideal candidate will be highly skilled in all aspects of data analytics, including mining, generation, and visualization. Additionally, this person should be committed to transforming data into readable, goal-oriented reports that drive innovation and growth.

Objectives of this role
Develop, implement, and maintain leading-edge analytics systems, taking complicated problems and building simple frameworks.
Identify trends and opportunities for growth through analysis of complex datasets.
Evaluate organizational methods and provide source-to-target mappings and information-model specification documents for datasets.
Create best-practice reports based on data mining, analysis, and visualization.
Evaluate internal systems for efficiency, problems, and inaccuracies, and develop and maintain protocols for handling, processing, and cleaning data.
Work directly with managers and users to gather requirements, provide status updates, and build relationships.

Responsibilities
Work closely with project managers to understand and maintain focus on their analytics needs, including critical metrics and KPIs, and deliver actionable insights to relevant decision-makers.
Proactively analyze data to answer key questions for stakeholders or yourself, with an eye on what drives business performance, and investigate and communicate which areas need improvement in efficiency and productivity.
Create and maintain rich interactive visualizations through data interpretation and analysis, with reporting components from multiple data sources.
Define and implement data acquisition and integration logic, selecting an appropriate combination of methods and tools within the defined technology stack to ensure optimal scalability and performance of the solution.
Develop and maintain databases by acquiring data from primary and secondary sources, and build scripts that will make our data evaluation process more flexible or scalable across datasets.