Business Data Analyst

Quest Technology Management; United States; Hybrid; USD 110,000 - 160,000; Full time

Job summary

Quest Technology Management seeks a Principal Business Data Analyst to lead data-driven decision support. You will collaborate with business teams to define needs, mentor analysts, and apply analytics techniques to generate insights.

You will develop forecasts, build dashboards, and communicate results to stakeholders, enabling optimized decisions while ensuring data governance and security.

Qualifications

• Bachelor’s degree or equivalent experience as stated in the job specs.
• 6+ years of demonstrated data analytics experience including querying and analyzing operational and/or financial data.
• Experience leading analytics projects in domains such as Financial Management, Forecasting, Risk Assessment, or Healthcare Management.
• Proficient in building complex data queries using SQL to join, filter, cleanse, and aggregate data; knowledge of no/low-code SQL applications.
• Proficient in designing data workflows and business-oriented data models against relational databases.
• Proficient in visualization and dashboard design to monitor KPIs and highlight trends.
• Experience using PowerBI, Cognos Analytics, Tableau, SAS or similar for data exploration.
• Experience applying statistical modeling to forecast and what-if scenarios.
• Strong strategic skills, business acumen, and curiosity to define requirements and deliver outcomes.
• Familiarity with Data Science techniques and notebooks (Jupyter) with Python and R.
• Excellent written and verbal communication, presentation, and analytical skills.
• For remote/hybrid roles, ability to engage in virtual environments with camera presence.

Responsibilities

• Lead engagements with business leaders to clarify needs and define requirements for strategic data use.
• Perform data exploration, analysis and statistical inference to identify trends and risks.
• Develop forecasts, regression models, what-if scenarios and actionable recommendations.
• Lead the creation of dashboards, visualizations and reports to monitor performance and automate where possible.
• Communicate insights clearly to advance organizational understanding.
• Collaborate with enterprise analytics and data management to articulate data needs and models.
• Produce workflows and data models using enterprise tools and integrating external data sets.
• Develop prototype models joining large data across domains for other analysts.
• Identify opportunities for machine learning and collaborate with Data Scientists to deliver value.
• Contribute to data inventory, metadata management, data quality remediation and governance.
• Maintain high standards and comply with data security and privacy policies.

Skills

Data analytics

SQL

Data visualization

PowerBI

Tableau

Cognos Analytics

Python

R

Mentoring

Data modeling

Education

Bachelor’s degree in statistics/analytics/economics/computer science or related field

Tools

PowerBI

Cognos Analytics

Tableau

SAS

Jupyter

R

Job description

Job Description

The Principal Business Data Analyst leads collaborations with business teams to determine needs and opportunities for leveraging data in support of business monitoring and decision management. This position mentors others to apply a range of analytics and statistical techniques to generate relevant and accurate insights through data exploration, modeling, analysis, and mining. Communicates findings effectively using visualizations, dashboards, and presentations with the goal of optimizing business decisions and outcomes.

• Lead engagements with business leaders and staff to clarify needs and define business requirements for strategic data use; where possible anticipates and proposes opportunities for analysis and exploration in support of business optimization and decision-making
• Support decision-makers by performing data exploration, analysis and statistical inference to identify and interpret trends and patterns in datasets and detect influences, opportunities and risks
• Develop forecasts, regression models, what-if scenarios and recommendations in consultation with leaders to support strategic/tactical planning and operational decision-making
• Lead the creation of dashboards, visualizations and reports to support business performance monitoring, automating where possible, to support stakeholders’ ability to be data driven
• Effectively communicates insights for business leaders and colleagues in order to advance the collective intelligence of the organization
• Work collaboratively with the enterprise analytics and information management team to articulate business needs for new/revised data models and views/access to the data
• Produce business-specific workflows and data models for analysis using enterprise analytics and data management tools, including the integration of external data sets that are approved for use
• Serve iterative business needs by developing prototype models that join large volumes of data across multiple data domains to deliver views for use by other analysts; understands the modeling techniques for ensuring integrity and responsiveness in those deliverables
• Identify business opportunities for machine learning and collaborates with Data Scientists to deliver value for the business unit
• Contribute to data inventory and stewardship efforts, including contributions to metadata management, data profiling, data quality remediation and data cleansing
• Maintain high standards and adhere to all enterprise policies and guidelines regarding data security and privacy, data management, data quality and data governance; regard data as an enterprise asset that is to be protected and used both strategically and appropriately

Job Specifications

• Bachelor’s degree in statistics, analytics, mathematics, economics, computer science, or related functional area; or equivalent experience
• 6+ years of demonstrated data analytics experience including querying and analyzing operational and/or financial data, generating insights and communicating those effectively with colleagues and leaders
• Prior experience in successfully leading analytics projects in one or more of the following domains/business functions: 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
• Proficient in building complex data queries using SQL in order to join, filter, cleanse,, and aggregate data; understanding of how no/low-code applications apply SQL concepts to do the same
• Proficient in designing data workflows and business-oriented data models against relational database structures
• Proficient in visualization and dashboard design techniques to create interfaces that monitor business performance against KPIs and highlight trends/patterns
• Proficient in using 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 forecasting and what-if scenarios
• Possesses strategic skills, business acumen, and curiosity to envision opportunities, document requirements, and collaborate for successful outcomes
• Capable of mentoring others to elevate the collective skills of the team
• Familiarity with Data Science techniques and experience in the use of notebooks (i.e., Jupyter) with programming languages like Python and R
• Excellent written and verbal communication, presentation, and analytical skills
• For roles that are remote (i.e., Work From Home (WFM)) or hybrid (i.e., partial onsite at a VSP location and WFM), must demonstrate a high level of engagement in virtual environments, including maintaining camera presence during meetings to support effective communication and team alignment

Preferred Skills

• Demonstrated ability to identify trends, determine root causes, evaluate performance variation, and develop meaningful quality insights from large, complex, fragmented datasets
• Healthcare quality and operational analytics knowledge
• Data storytelling and executive communication skills, capable of translating technical findings into concise, actionable insights
• Data governance expertise, including data validation, metric definition, reporting standards, and regulatory considerations