Associate Data Analyst

UST is a mission-driven technology company that helps clients create transformative, human-centered solutions through innovation and agility. The company is seeking an Associate Data Analyst to extract, clean, validate, and analyze data from multiple source systems, build dashboards and reports, investigate data quality issues, and support analytics delivery with client stakeholders and internal teams.

Responsibilities:

• Perform data profiling, trend analysis and ad-hoc analysis to answer business questions
• Build and maintain dashboards and recurring reports using standard BI tools
• Translate business requirements into data queries, metric definitions and report specifications
• Investigate and resolve data quality issues, escalating complex discrepancies to the lead
• Document data sources, business logic, report definitions and standard operating procedures
• Collaborate with client stakeholders, data engineers and senior analysts on delivery of analytics work
• Support junior analysts with queries on tools, data sources and reporting standards
• Adhere to client data security, privacy and compliance standards (including HIPAA/PHI handling where applicable)

Requirements:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering or a related discipline
• 2–4 years of experience in data analysis, business intelligence or reporting. Strong hands-on proficiency in SQL for querying and data manipulation
• Practical experience with visualization tools such as Tableau, Power BI or SAS reporting
• Working knowledge of Excel (advanced functions, pivots) and basic scripting in Python or R
• Understanding of relational databases, data warehousing and ETL concepts
• Good analytical, problem-solving and communication skills with the ability to work with client stakeholders
• Must be authorized to work in the USA and available to work from the client location
• Familiarity with US healthcare / payer domain data
• Relevant certification in Tableau, Power BI or SQL
• Preferred / Value-Add Exposure to cloud data platforms (AWS, Azure or GCP) or modern data stacks (Snowflake, Databricks)