Senior Data Analyst
| Company | Strata Decision Technology |
|---|---|
| Location | Chicago, IL, USA, St. Louis, MO, USA |
| Salary | $87000 – $105000 |
| Type | Full-Time |
| Degrees | |
| Experience Level | Mid Level, Senior |
Requirements
- 4+ years experience using statistical data analysis techniques, ideally in the healthcare or financial sectors
- Experience working with large, complex data sets
- Strong applied statistics skills, such as distributions, statistical testing, regression, etc.
- Experience composing a compelling data story with conclusions and recommendations based on inferences and insights from the data
- Ability to present results of analysis to differing audiences from executives to analysts
- Ability to accurately translate business problems into data requirements
- Experience working with customers to investigate data challenges and collaborating with customers on solution development
- Strong scripting and programming skills using common data science languages such as Python
- Experience with data visualization tools, such as Tableau or PowerBI
- Proficiency in using advanced SQL techniques such as common table expressions and window functions
- Experience with cloud computing services such as Snowflake, AWS, or Sagemaker
- Data-oriented personality, who is a self-starter with strong accountability and project management for tasks
- Ability to travel up to 10%
Responsibilities
- Applying data mining techniques and statistical analysis to healthcare and financial data across our customer base
- Extracting, cleansing, and validating the data used for analyses
- Working with customers to define the business problem, translate this into data requirements, analyze the data, and share insights
- Creating analytics that tell a compelling data story
- Collaborating with the data science team, product management, customers, sales, and data engineering to enhance Strata’s data products
- Supporting customers to answer deep-dive data questions related to Strata’s data products
- Developing and maintaining automated processes and workflows to improve efficiency and consistency with handling data
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Creating logic for and testing automated anomaly detection systems and constant tracking of its performance
Preferred Qualifications
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No preferred qualifications provided.