Conversational Reporting & Analytics

Senior Analyst – Conversational Reporting & Analytics

Role Overview

The Senior Analyst – AI-Enabled Reporting & Analytics is a hands-on individual contributor responsible for building, maintaining, and enhancing commercial reporting and analytics solutions. The role focuses on delivering accurate, timely, and high-quality BI reports and datasets, while supporting foundational AI-enabled and conversational reporting capabilities.

The Senior Analyst works closely with Managers and Senior Analysts to translate business requirements into dashboards, datasets, and analytical outputs, ensuring adherence to analytics standards, data governance, and quality expectations.

Key Responsibilities

1. Commercial Reporting & Analytics Execution

• Develop and maintain commercial performance reports supporting Sales, Marketing, and Commercial Operations.
• Translate clearly defined business requirements into KPIs, dashboards, and analytical outputs.
• Support recurring performance reviews by delivering accurate and well-documented analytics.

2. BI Development & Dashboard Build

• Build and enhance Power BI/Angular reports and dashboards, including:
  • Report layouts and visual design
  • DAX measure development under guidance
  • Dataset usage and basic performance optimization
• Apply standardized KPI definitions, metrics, and reporting templates.
• Validate reports for accuracy, usability, and consistency.

3. Analytics Data Preparation

• Develop and maintain analytics datasets using:
  • SQL-based transformations
  • Basic dimensional and semantic modeling concepts
• Support data pipelines and refresh processes in:
  • Databricks and/or Dataiku
  • Cloud-based analytics platforms
• Partner with Managers to identify and resolve data quality issues.

4. Performance Analysis & Insights Support

• Perform standard performance analyses, including:
  • Sales, campaign, and activity performance tracking
  • Trend and variance analysis
• Prepare data summaries, charts, and supporting analysis for stakeholder presentations.
• Document assumptions, calculations, and data limitations clearly.

5. AI-Enabled & Conversational Reporting (Support Role)

• Support AI-enabled and conversational analytics initiatives by:
  • Preparing and validating datasets used for conversational reporting
  • Testing and validating chatbot or natural-language query outputs
• Assist with building basic natural-language reporting views under defined frameworks.
• Ensure outputs are accurate, traceable, and compliant with reporting standards.

6. Stakeholder & Team Collaboration

• Work with Managers to support day-to-day analytics requests.
• Participate in requirement discussions and clarification sessions.
• Collaborate with Analysts and peer Senior Analysts to ensure delivery consistency.

7. Quality, Governance & Documentation

• Follow established analytics development, documentation, and validation standards.
• Ensure compliance with data governance, security, and regulatory requirements.
• Contribute to documentation, reusable assets, and reporting best practices.

Qualifications & Experience

Education

• Bachelor’s degree in Engineering, Computer Science, Information Systems, Statistics, Economics, or related field
• Master’s degree preferred

Experience

• 4–6+ years of experience in BI, reporting, or commercial analytics
• Hands-on experience developing dashboards and analytics deliverables
• Exposure to pharmaceutical or life sciences commercial analytics preferred
• Experience working in structured, regulated environments is a plus

Technical Skills

Required

• Hands-on experience with Power BI/Angular (report development, visuals, basic DAX)
• Strong SQL skills for data extraction and transformation
• Experience working with analytics datasets and reporting models
• Familiarity with commercial performance data (sales, marketing, field activity)
• Strong attention to data quality and detail

Desired

• Exposure to AI-enabled or conversational reporting concepts
• Basic familiarity with natural-language querying or AI-assisted analytics
• Python exposure for analytics or automation
• Experience with Databricks, Dataiku, or cloud analytics platforms