Senior Data Analyst
Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 9, 2026.
Senior Data Analyst
Department: Product Development
Reports to: Director of Data Engineering
Suvoda’s Data Services team is responsible for data delivery from all applications in the clinical platform to our customers. The team is responsible for the collection, structuring, scrubbing, aggregation, and secure delivery of this data. We also provide our customers value-added services such as statistical and ML driven data analytics, visualization and tabular reporting. We are looking for a highly experienced Senior Data Analyst to drive delivery of our future data strategy.
Responsibilities:
- Lead data discovery efforts, where you will help internal and external stakeholders in finding relevant data assets by providing guidance on queries, business logic and data lineage analysis
- Investigate and analyze existing data in databases to interpret quality of existing content
- Ensure data accuracy, completeness, and consistency through ongoing data profiling, cleansing, and enrichment
- Manage cross functional data governance policies by cataloging, maintaining, and analyzing data to improve its discoverability, reliability, and security
- Analyze data and create reports and dashboards
- Develop new data products and ML based analytics
- Grow the data literacy of the team through a combination of coaching and documenting
- Understand and apply data privacy principles to minimize and secure any sensitive data
Requirements:
- Bachelor's degree in Computer Science, Mathematics, Statistics, Data Science or related disciplines, Master's degree in Statustucs, Data Science, or related discplines preferred
- Experience working with lefger-based financial data or clinical trial data preferred
- At least 5 years' experience with SQL and Excel
- At least 3 years' experience with data profiling and cataloging tools such as OpenMetadata, AWS Glue Data Quality, or dbt test
- Familiarity with Python and Python data quality libraries such as Great Expectations, Spark Expectations
- Strong understanding of statistical concepts (hypothesis testing, regression analysis, Analysis of Variance)
- Ability to identify complex problems, analyze data to find root causes, and propose data-driven solutions
- Excellent written and verbal communication skills to effectively present findings and insights to non-technical audiences
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