Data Analyst

SysAid is a dynamic SaaS company specializing in IT Service Management. We are recognized as a leading innovator in the industry, featured in the Gartner Magic Quadrant for ITSM, and honored with AWS's prestigious Rising ISV Star Award. With over 4,000 clients across 140 countries and a daily impact on over 9 million end-users, we are committed to transforming the ITSM landscape.

Our mission is to liberate organizations by putting AI to work for them and their people.

We seek a Data Analyst to support product development with a special focus on owning the data quality used for AI product development while working closely with stakeholders across different departments.

Key Responsibilities:

Create and maintain reports and datasets required to support SysAid Copilot (AI) development.
Create visibility into our products and services for various use cases and teams at SysAid.
Promote data-driven decisions by analyzing data quality and helping set KPIs to monitor AI features health checks, conducting root cause analysis, discovering anomalies, and improving.
Manage multiple data initiatives and projects, both ongoing and ad hoc.
Recommend tools and data analysis techniques, present new approaches to data analytics
Work closely with various teams - Senior Management, Product Managers, Operations Managers, Research, SW developers, and more.

Requirements:

3+ years of experience as an analyst in a high-tech company, demonstrating a strong understanding of data analysis principles and methodologies.
Mastery of SQL, with the ability to write complex queries and manipulate large datasets efficiently.
Proficiency in Python and statistical modeling.
Extensive hands-on experience with BI tools.
Extraction, transformation, and loading of data from various sources.
Passion for leveraging advanced analytics techniques to extract meaningful insights and drive strategic decision-making.
Familiarity with prompt engineering techniques.
BA / B.Scs. in Industrial Engineering and Management / Information Systems/ Engineering / Statistics or a similar background.