Technology Data Analyst, Factset

• Bachelor’s degree: Finance, Economics, Computer Science, Statistics, Engineering (Master’s preferred)
• 5 years of relevant experience minimum, ideally within the Technology or broader TMT sectors with focus on technology
• Strong proficiency in data analysis, modelling, and visualization tools (e.g., Excel, Power BI/Tableau, SQL, Python) for data extraction, transformation, analysis, and workflow automation
• Hands-on experience preparing data for statistical and machine learning models
• Familiarity with distributed data systems and cloud platforms (any of AWS, Azure, Databricks, Snowflake)
• Experience building dashboards and data visualizations (e.g., Tableau, Power BI or similar)
• Exceptional analytical, quantitative, and organizational skills with the ability to synthesize complex data into clear insights
• Solid written and verbal communication skills, including the ability to translate data findings into actionable business narratives

Desirable

• Join the Deep Sector TMT team as the Technology Data Analyst for FactSet’s Technology data offering
• You’ll help support the evolution of FactSet’s Technology data offering – maintaining and enhancing our existing Tech-sector datasets, integrating new sources into our client-facing applications, data feeds and APIs , and translating client workflows into best-in-class product features and workflow solutions
• In this role, you will be part of a team to develop and execute on a strategic roadmap for FactSet’s Technology sector offering
• Data Management: Participate directly and indirectly in the extraction, cleaning, and transformation of large, complex datasets, ensuring accuracy, consistency, and timeliness
• Data Validation: Take control of our data products, utilizing human-in-the-loop data curation and validation software to ensure our products evolve with changing standards and reporting requirements, while also delivering timely, accurate and complete products
• Client Engagement: Partner with sales/consulting, data providers, and clients across FactSet’s user base to understand their workflows, pain points, and feature requests; and to position our offering vs. their current needs and competitor solutions
• Requirement Definition: Translate qualitative and quantitative client insights into clear product requirements, specifications, and user stories that delight and exceed client expectations
• Cross-Functional Collaboration: Work closely with engineering, QA, UX, other content developers as well as specialized data teams to deliver value to clients. Presentation & Training: Develop and deliver compelling presentations and demos of FactSet’s Technology sector offerings—in person and virtually—to both internal stakeholders and external clients Partnerships and Acquisition Opportunities: Actively monitor and the competitive landscape for data partnership or acquisition opportunities to strengthen FactSet’s Technology offering
• Team Development: Mentor and train team members in content collection and integration processes, product workflows, and best practices
• Data Ownership: Identify areas of opportunity where FactSet can own and operate data collection and reduce reliance on third-party data spend