The Antwi Group is seeking an experienced, analytical, detail-oriented, and business-focused Senior Data Analyst to join our Data & Business Intelligence Department.
Working under the direction of the Director / Manager of Data & Business Intelligence and Business Intelligence Manager, the Senior Data Analyst will perform advanced analysis, develop reporting solutions, evaluate business performance, investigate trends and variances, support forecasting, validate data, develop key performance indicators, and translate complex information into clear business insights.
The Senior Data Analyst will work with information across The Antwi Group’s creative, entertainment, music, media, technology, production, distribution, sales, marketing, customer-service, administrative, and related businesses.
The position will collaborate with leadership and departmental stakeholders to define analytical requirements, identify appropriate data sources, develop analytical methodologies, create reports and dashboards, investigate business questions, and communicate findings.
The Senior Data Analyst may also review work produced by other analysts, mentor developing team members, establish analytical best practices, and lead complex analytical projects.
This position requires advanced analytical ability, strong SQL and data-management skills, statistical understanding, business judgment, communication, objectivity, accuracy, curiosity, and confidentiality.
Key Responsibilities
- Perform advanced business analysis.
- Analyze complex datasets.
- Develop analytical methodologies.
- Investigate business-performance trends.
- Conduct variance analysis.
- Support forecasting.
- Develop and validate KPIs.
- Build recurring reports.
- Develop analytical dashboards.
- Write and optimize analytical queries.
- Validate data accuracy.
- Investigate data-quality issues.
- Develop data models for analysis.
- Combine information from approved data sources.
- Conduct root-cause analysis.
- Support executive reporting.
- Prepare analytical presentations.
- Document analytical methods.
- Review reports and analyses for accuracy.
- Mentor analysts.
- Support self-service business intelligence.
- Identify opportunities for reporting automation.
- Protect confidential information.
- Communicate significant analytical findings.
- Support departmental analytical standards.
Analytical Workflow
Analytical assignments may follow:
Business Question → Requirements → Data → Validation → Analysis → Interpretation → Communication → Follow-Up
Business Questions
Assignments may address questions such as:
- Why did performance change?
- Which products or services are growing?
- Where are operational delays occurring?
- Which customer groups behave differently?
- What factors are associated with conversion?
- How is performance changing over time?
- Where are resources being used?
- What requires management attention?
Requirements Definition
Before beginning significant analysis, the Senior Data Analyst may establish:
- Business objective
- Scope
- Audience
- Required metrics
- Data sources
- Time period
- Required segmentation
- Analytical methodology
- Delivery deadline
- Known limitations
Data Acquisition
The Analyst may work with approved information from:
- CRM systems
- Financial systems
- Marketing platforms
- Websites
- Customer-service systems
- Project-management systems
- Production systems
- Distribution platforms
- Operational databases
- Human Resources systems
- Other approved sources
SQL & Query Development
Responsibilities may include:
- Writing SQL queries
- Joining datasets
- Aggregating information
- Developing reusable queries
- Creating analytical datasets
- Validating query outputs
- Improving query efficiency
Production database changes should remain subject to appropriate IT authorization and change-control procedures.
Data Preparation
Analysis may require:
- Data cleaning
- Standardization
- Classification
- Transformation
- Aggregation
- Deduplication
- Validation
- Derived calculations
Data Quality
The Analyst should identify potential:
- Missing records
- Duplicate records
- Invalid values
- Unexpected changes
- Inconsistent classifications
- Stale information
- Broken relationships
- Outliers requiring investigation
Data Quality Investigation
Potential issues may follow:
Issue → Source → Validation → Business Impact → Responsible Owner → Correction → Verification
Source-System Integrity
The Analyst should not alter authoritative source records without proper authorization.
KPI Development
The Senior Data Analyst may help define:
KPI → Business Definition → Formula → Source → Frequency → Owner → Interpretation
KPI Validation
Before a KPI is widely used, the Analyst should confirm:
- Calculation accuracy
- Appropriate source data
- Consistent business definition
- Historical behavior
- Known limitations
- Appropriate interpretation
Performance Analysis
The Analyst may evaluate:
- Revenue
- Sales
- Marketing
- Customer activity
- Operations
- Projects
- Production
- Distribution
- Customer service
- Workforce indicators
- Vendor performance
- Other approved areas
Trend Analysis
Analysis may compare:
- Daily performance
- Weekly performance
- Monthly performance
- Quarterly performance
- Annual performance
- Year-over-year changes
- Business-unit trends
- Customer-segment trends
- Product or service trends
Variance Analysis
The Analyst may investigate differences between:
- Actual and target
- Actual and budget
- Current and previous periods
- Forecast and actual
- Business units
- Channels
- Customer segments
- Operational benchmarks
Root-Cause Analysis
Root-cause work may follow:
Observed Change → Hypotheses → Data Testing → Contributing Factors → Findings → Limitations
The Analyst should distinguish between:
- Correlation
- Association
- Demonstrated causation
- Reasonable hypothesis
- Unverified assumption
Statistical Analysis
Depending on the assignment, analysis may involve:
- Descriptive statistics
- Distributions
- Correlations
- Confidence intervals
- Regression
- Hypothesis testing
- Segmentation
- Time-series analysis
- Other appropriate methods
Forecasting
The Analyst may support forecasting involving:
- Revenue
- Sales
- Demand
- Customer activity
- Production volume
- Workload
- Staffing requirements
- Operational capacity
Official financial forecasts should be coordinated with Finance & Accounting.
Forecast Evaluation
Forecast performance may be evaluated using appropriate measures and historical outcomes.
Assumptions and uncertainty should be documented.
Scenario Analysis
The Analyst may model:
- Base cases
- Growth cases
- Downside cases
- Capacity scenarios
- Pricing scenarios
- Operational scenarios
- Other approved alternatives
Executive Reporting
The Analyst may prepare information for senior leadership involving:
- Performance summaries
- Trends
- Significant variances
- Key drivers
- Emerging risks
- Opportunities
- Forecast information
- Analytical findings
Management Reports
Recurring reports should be:
- Accurate
- Consistent
- Timely
- Documented
- Appropriate for the intended audience
Dashboard Development
The Analyst may develop dashboards using approved BI platforms.
Dashboard development may include:
- Data preparation
- Measures
- Calculations
- Filters
- Visualizations
- Validation
- Documentation
- User testing
Data Visualization
Appropriate visualizations may include:
- Tables
- Scorecards
- Line charts
- Bar charts
- Scatter plots
- Distribution charts
- Maps where appropriate
- Other analytical graphics
Visual design should accurately represent the underlying information.
Sales Analytics
The Analyst may examine:
- Leads
- Opportunities
- Pipeline
- Conversion
- Sales activity
- Revenue
- Sales cycles
- Customer segments
- Account performance
Marketing Analytics
Analysis may include:
- Website traffic
- Campaign performance
- Engagement
- Lead generation
- Conversion
- Customer acquisition
- Channel performance
- Audience behavior
Customer Analytics
The Analyst may examine:
- Acquisition
- Retention
- Engagement
- Customer segments
- Service usage
- Customer lifecycle
- Support activity
Customer Service Analytics
Reporting may analyze:
- Case volume
- Response time
- Resolution time
- Escalations
- Issue categories
- Recurring problems
- Service trends
Project Analytics
Working with Project Management, analysis may involve:
- Project schedules
- Milestones
- Completion rates
- Resource utilization
- Risks
- Delays
- Project outcomes
Production Analytics
Analysis may involve:
- Production volume
- Scheduling
- Capacity
- Resource utilization
- Delays
- Completion
- Operational efficiency
Music & Distribution Analytics
Where applicable, authorized analysis may examine:
- Release activity
- Catalog performance
- Distribution activity
- Platform performance
- Territory activity
- Artist or label activity
- Audience or consumption trends
- Operational revenue indicators
Royalty calculations and official financial reporting remain with appropriate Finance and business-unit functions.
Workforce Analytics
Working with Human Resources, authorized aggregated analysis may include:
- Headcount
- Hiring
- Turnover
- Staffing
- Training
- Workforce planning
Access to personally identifiable employee information must remain appropriately restricted.
Financial Analytics
Working with Finance, analysis may include:
- Revenue trends
- Expense trends
- Budget comparisons
- Business-unit performance
- Forecast support
- Management reporting
Official accounting judgments and financial statements remain with Finance.
Operational Analytics
The Analyst may evaluate:
- Cycle time
- Work volume
- Completion rates
- Error rates
- Service levels
- Capacity
- Resource utilization
- Process performance
Analytical Automation
The Senior Data Analyst may automate repetitive analytical work involving:
- Data preparation
- Calculations
- Report generation
- Quality checks
- Data validation
- Scheduled reporting
Programming
Depending on the environment, analytical programming may use:
- SQL
- Python
- R
- Spreadsheet automation
- Approved BI scripting languages
- Other authorized analytical tools
Code Quality
Analytical code should be:
- Readable
- Documented
- Tested
- Reproducible where practical
- Maintained appropriately
Analytical Documentation
Significant work should document:
- Purpose
- Data sources
- Definitions
- Methodology
- Calculations
- Assumptions
- Limitations
- Date range
- Refresh requirements
Peer Review
The Senior Data Analyst may review analytical work produced by other team members.
Review may examine:
- Logic
- Data sources
- Calculations
- Methodology
- Interpretation
- Visualization
- Documentation
Mentoring
The Senior Data Analyst may support developing analysts through:
- Technical guidance
- Query review
- Analytical methodology
- Data-quality practices
- Visualization guidance
- Business interpretation
- Documentation standards
Self-Service Analytics
The Analyst may help develop standardized datasets, dashboards, documentation, and training materials for authorized business users.
Artificial Intelligence & Advanced Analytics
Where approved, the Analyst may support:
- Predictive models
- Machine-learning analysis
- AI-assisted analytics
- Natural-language analysis
- Automated classification
- Other advanced analytical techniques
Appropriate validation and governance must be applied.
Model Limitations
Predictive or statistical models should document relevant:
- Assumptions
- Training data
- Validation
- Accuracy
- Limitations
- Appropriate use
Data Privacy
The Analyst must follow approved privacy and information-handling procedures.
Data Security
The Analyst must not:
- Share restricted data with unauthorized individuals.
- Circumvent access controls.
- Store sensitive information in unauthorized systems.
- Share credentials.
- Export restricted datasets without appropriate authorization.
Analytical Integrity
The Senior Data Analyst must not knowingly:
- Manipulate analysis to support a predetermined conclusion.
- Conceal material limitations.
- Fabricate data.
- Alter metrics without authorization.
- Selectively exclude material information to mislead.
- Present speculation as established fact.
Confidentiality
The Senior Data Analyst may have access to:
- Financial information
- Customer information
- Employee information
- Business plans
- Sales information
- Marketing information
- Production information
- Distribution information
- Contracts
- Unreleased projects
- Strategic information
Such information must only be accessed and used for legitimate authorized company purposes.
Cross-Department Collaboration
Data & Business Intelligence Leadership — analytical strategy and priorities.
Business Intelligence Analysts — dashboard and reporting development.
Data Analysts — analysis and reporting.
IT & Digital Systems — databases, integrations, infrastructure, and security.
Finance & Accounting — financial analytics.
Sales — commercial analytics.
Marketing — campaign and audience analytics.
Human Resources — authorized workforce analytics.
Operations & Administration — operational analytics.
Project Management — project analytics.
Customer Service & Support — service analytics.
Production & Creative Teams — production analytics.
Business Units — specialized analytical requirements.
Qualifications
- Bachelor’s degree in Data Analytics, Statistics, Mathematics, Economics, Computer Science, Information Systems, Finance, Business Analytics, Engineering, or a related quantitative field required or equivalent substantial professional experience.
- Several years of professional data-analysis, business-intelligence, statistical-analysis, reporting, or related experience.
- Advanced SQL skills.
- Strong spreadsheet skills.
- Experience with business intelligence and visualization tools.
- Strong analytical and statistical ability.
- Experience working with large or complex datasets.
- Strong data-quality and validation skills.
- Excellent written and verbal communication.
- Ability to explain complex analysis to nontechnical audiences.
- Strong business judgment.
- Excellent attention to detail.
- High level of integrity and confidentiality.
Preferred Skills
Experience with one or more of the following is highly desirable:
- SQL
- Python
- R
- Power BI
- Tableau
- Looker
- Excel
- Statistical modeling
- Forecasting
- Data visualization
- Data warehouses
- Data modeling
- ETL / ELT
- Cloud analytics
- CRM analytics
- Web analytics
- Entertainment analytics
- Music analytics
- Media analytics
Professional Expectations
The successful candidate should demonstrate:
- Analytical rigor
- Accuracy
- Curiosity
- Objectivity
- Business judgment
- Technical ability
- Communication
- Integrity
- Organization
- Problem solving
- Accountability
- Confidentiality
- Strong attention to detail
Career Development
A potential career path may include:
Senior Data Analyst → Business Intelligence Manager → Director / Manager of Data & Business Intelligence → Senior Director / Head of Data & BI
Employees may also develop toward Data Science, Analytics Engineering, Data Governance, Advanced Analytics, Business Strategy, or Analytics Leadership.
Location
Poconos, Pennsylvania
The position may involve office-based analytical work and collaboration with teams across company locations and business units.
Projects, system implementations, business reviews, or operational requirements may occasionally require travel, evening, weekend, holiday, or irregular-hour availability.
Employment Type
Full Time
Department
Data & Business Intelligence
Reports To
Director / Manager of Data & Business Intelligence / Business Intelligence Manager
About The Antwi Group
The Antwi Group is a growing organization operating across creative, entertainment, media, and related business sectors. Our teams bring together creative talent, technical expertise, management, financial discipline, technology, production, operations, and business development to build projects and opportunities designed for long-term growth.
Application
Interested candidates should submit an application outlining their education, data-analysis, business-intelligence, statistical, reporting, programming, visualization, forecasting, or related professional experience and other relevant qualifications.
Applicants may also be asked to provide a résumé/CV, professional references, and examples or descriptions of analytical projects, dashboards, reports, data models, statistical work, or programming projects that they are legally permitted to share.
Applicants should not submit confidential datasets, proprietary dashboards, source code belonging to another organization, database credentials, customer records, employee information, trade secrets, unreleased financial information, or other confidential materials belonging to current or previous employers, clients, vendors, or business partners.
The Antwi Group is an equal opportunity employer. We consider qualified applicants without regard to characteristics protected by applicable law.