Our vision is clear - arming every company with the insight to ensure every piece of software built or bought is safe and every threat detected. An innovative vision requires innovative talent to help forge this transformational journey at ReversingLabs. ReversingLabs is recognized by the cybersecurity industry as a leader in innovation. The $56M investment from Crosspoint Capital will support our growth and innovation efforts to build scalable, automated, and intelligent software security solutions.

We are looking for a passionate Big Data Analyst with a keen eye for detail and the ability to understand data. The successful candidate will turn data into information, information into insight, and insight into business decisions.

You will be responsible for developing and managing our master data set, developing reports, and troubleshooting data issues. To do well in this role, you need a keen eye for detail, some experience as a data analyst, and an understanding of popular data analysis tools and databases.

We offer file reputation records for over 50 billion samples, making our database the largest reputation database. Our customers receive the information through more than 50 REST APIs and Feeds. By performing hands-on data research, you will provide insights, uncover potential issues, and enhance the decision-making process. You will perform complex analysis on large data sets using appropriate data analysis techniques and tools with a strong focus on quality.

Responsibilities

Gathering data from various sources and then cleansing, organizing, processing, and analyzing it to extract valuable insights and information
Working with various database types to handle large amounts of data in structured, semi-structured, and unstructured form
Developing reports and dashboards (charts, tables, ...) with data analysis results to help different audiences make better decisions
Identifying, analyzing, and interpreting trends or patterns in complex data sets
Understanding sources and lineage of data to control the quality of our data sets
Collaborating with team members to prioritize business and information requirements
Ensure data quality by implementing data validation and cleansing processes
Performing routine analysis tasks to support day-to-day business
Applying statistical analysis methods for consumer data research and analysis purposes
Maintain and improve existing data pipelines
Closely collaborating with both the IT teams and customer-facing teams to accomplish company goals and prove value to our customers

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