Principal Business Data Analyst

VSP Vision Care•Cynthian, OH

1d•$84,000 - $141,750

About The Position

The Principal Business Data Analyst leads collaborations with business teams to identify needs and opportunities for using data to support business monitoring and decision-making. The role mentors others in applying analytics and statistical techniques to produce relevant, accurate insights through data exploration, modeling, analysis, and mining. It communicates findings through visualizations, dashboards, and presentations to help optimize business decisions and outcomes. The analyst partners with business leaders and staff to define requirements, anticipates opportunities for analysis, and supports strategic and operational decisions with data exploration, statistical inference, forecasts, regression models, and what-if scenarios. The role leads the development of dashboards, visualizations, and reports, and collaborates with enterprise analytics and information management teams on data models and access to data. The position develops business-specific workflows and data models using enterprise analytics and data management tools, including approved external datasets. It creates prototype models joining data across domains, identifies machine-learning opportunities in collaboration with Data Scientists, and contributes to data inventory, stewardship, metadata management, profiling, quality remediation, and cleansing. The analyst follows enterprise policies for data security, privacy, management, quality, and governance.

Requirements

Bachelor’s degree in statistics, analytics, mathematics, economics, computer science, or a related functional area, or equivalent experience.
At least 6 years of data analytics experience, including querying and analyzing operational and/or financial data, generating insights, and communicating them effectively.
Experience leading analytics projects in at least one of these domains: financial management and forecasting, risk assessment, insurance utilization and pricing, supply chain optimization, retail management, eCommerce management, consumer behavior analysis, marketing optimization, or healthcare management.
Proficiency building complex SQL queries to join, filter, cleanse, and aggregate data, and understanding how no/low-code applications apply SQL concepts.
Proficiency designing data workflows and business-oriented data models against relational database structures.
Proficiency in visualization and dashboard design to monitor business performance against KPIs and highlight trends and patterns.
Proficiency with data exploration and analysis platforms such as PowerBI, Cognos Analytics, Tableau, SAS, or similar.
Experience applying statistical modeling to evaluate complex business problems and develop forecasts and what-if scenarios.
Strategic skills, business acumen, and curiosity to envision opportunities, document requirements, and collaborate toward successful outcomes.
Ability to mentor others and elevate team skills.
Excellent written and verbal communication, presentation, and analytical skills.

Nice To Haves

Familiarity with Data Science techniques and experience using notebooks such as Jupyter with programming languages such as Python and R.

Responsibilities

Lead engagements with business leaders and staff to clarify needs and define business requirements for strategic data use, and identify opportunities for analysis and exploration.
Perform data exploration, analysis, and statistical inference to identify and interpret trends and patterns, and detect influences, opportunities, and risks.
Develop forecasts, regression models, what-if scenarios, and recommendations with leaders to support planning and operational decision-making.
Lead creation of dashboards, visualizations, and reports for business performance monitoring, automating them where possible.
Communicate insights effectively to business leaders and colleagues.
Collaborate with enterprise analytics and information management teams to articulate business needs for new or revised data models, views, and data access.
Produce business-specific analysis workflows and data models using enterprise analytics and data management tools, including approved external datasets.
Develop prototype models that join large volumes of data across multiple domains, with attention to integrity and responsiveness.
Identify business opportunities for machine learning and collaborate with Data Scientists to deliver value.
Contribute to data inventory and stewardship, metadata management, data profiling, data quality remediation, and data cleansing.
Follow enterprise policies and guidelines for data security, privacy, management, quality, and governance.