WHAT DOES AN ANALYTICS DO?

Published: May 15, 2025 - The Analytics Professional analyzes complex data sets to uncover trends, patterns, and insights that support strategic business decisions. This role focuses on transforming raw data into actionable information through the development of dashboards, models, and reports. The individual contributes to performance improvement, process optimization, and data-driven forecasting across the organization.

A Review of Professional Skills and Functions for Analytics

1. Strategy and Analytics Analyst Duties

  • Market Analysis: Understand product and market changes and implications for the strategy, using available industry data sources
  • Supplier Research: Research suppliers, competitors, government/regulations, and supply risks for the portfolio
  • Insight Communication: Communicate findings and insights to stakeholders with a point of view and a desire to enable data-driven decisions
  • Project Support: Support a variety of projects across the organization, including design sprints and annual board meetings
  • Meeting Preparation: Review supplier background materials to prepare sourcing executives for supplier meetings
  • Portfolio Review: Support review of generic portfolio (e.g., annual cost savings, potential changes in exclusivity, modeling changes in purchasing methodologies) and standing supplier appointments
  • Data Compilation: Compile data from multiple sources into meaningful communication with a proposal for recommended action
  • Decision Innovation: Contribute to internal innovation efforts to make decisions faster and more effectively
  • Financial Forecasting: Collaborate on budgeting and forecasting activities for CVS Health and Cardinal Health
  • Change Management: Support change management efforts to help adopt new information assets

2. Data and Analytics Architect Details

  • Cloud Migration: Contribute to a large-scale enterprise analytics solution migration to Azure
  • Project Leadership: Fulfill an important and influential role in the project
  • Architecture Analysis: Analyse Enterprise transformation programs from an architectural level
  • Workload Assessment: Analyse workload migration between technology stacks and architectural patterns
  • Azure Implementation: Implementing Azure Cloud Solutions within an established enterprise environment
  • DevOps Practices: Guide and implement DevOps Best Practices, i.e., CI/CD, DataOps
  • ETL Assessment: Design and undertake data and ETL workload assessments for migration
  • Technical Documentation: Create Technical Design Documentation
  • Vendor Engagement: Engage with Cloud vendor resources and partners to progress customer solutions

3. Analytics Associate Responsibilities

  • Client Solutions: Contribute to the success of clients by understanding their challenges and tailoring solutions to their needs
  • Effective Communication: Communicate effectively with clients and the team to deliver on and meet client needs
  • Project Execution: Produce quality work promptly across multiple projects to drive impact
  • Business Development: Support the growth of the business through business development activities, including deck creation, research, and more
  • Technical Expertise: Work to demonstrate significant technical experience within a specific skill or platform in the first year
  • Growth Mindset: Exhibit a growth mindset through continuous focus on the development plan
  • Team Collaboration: Collaborate and consult with peers, colleagues, managers and regulators to resolve issues and achieve goals
  • Team Management: Manage a team to assist with the Wells Fargo Quantitative Analytics program

4. Analytics Consultant Job Summary

  • Model Development: Support the development, testing and maintenance of risk and provision models
  • Statistical Modeling: Develop, maintain and continuously improve statistically robust and reliable models, appropriate for intended use (behavior scorecards, capital, stress test and provisioning)
  • Regulatory Compliance: Compliant with internal policies and external regulations (Basel, EBA, IFRS9)
  • Model Implementation: Ensure the correct implementation of models into the DLL’s risk infrastructure systems
  • Policy Translation: Translating policies and models into technical requirements, testing and reporting on the results
  • Assumption Analysis: Underpin modelling assumptions, assess their impact on model outcome and increase the understanding of a model’s limitations and weaknesses
  • Data-Driven Recommendations: Develop recommendations based on the performed quantitative analysis
  • Stakeholder Communication: Effectively communicate results to the relevant stakeholders in both written and verbal form (i.e., the business representatives, senior management, CRO staff, audit, ECB, Model Validation)
  • Risk Assessment: Identify drivers of risk costs and estimate the expected losses for different customer segments
  • Business Analysis: Execute other business analyses to identify and manage both risks and opportunities to improve business performance
  • Quantitative Optimization: Perform quantitative analysis to optimize DLL’s automated customer screening and credit scoring systems, incorporating both efficiency and effectiveness measures

5. Analytics Developer Accountabilities

  • Data Management: Manage the planning, design, and development of data marts, data warehouses, dashboards, and reports to align with business requirements
  • Requirements Definition: Define business requirements for data warehousing and analytics
  • ETL Operations: Operate ETL tools to extract, transform, and load data from various sources, including transactional systems and databases
  • Reporting Solutions: Develop reporting and visualization solutions within the existing systems
  • Statistical Tools: Utilize data modeling, data transfer, and statistical modeling tools
  • User Collaboration: Collaborate with internal business users to understand their needs and identify opportunities for improvement
  • Functionality Implementation: Work with consulting resources to implement new or enhanced functionality
  • Decision Support: Ensure that data solutions meet business needs and support data-driven decision-making processes

6. Analytics Director Functions

  • Client Relationship: Responsible for establishing strong client relationships to drive client retention and business growth
  • Proposal Writing: Understand client needs and write proposals by identifying the right analytics solution that serves client needs
  • Analytics Expertise: Be a strong partner and subject matter expert in the domain of analytics within the organization
  • Project Management: Lead end-to-end project management from design to data collection to modeling to delivery
  • Model Interpretation: Interpret and validate model results and build reports and presentations for senior client stakeholders
  • Stakeholder Presentation: Present the findings and recommendations to senior client stakeholders
  • Custom Modeling: Run custom models to solve specific client business questions
  • Project Delivery: Collaborate with COE to ensure the project is delivered to specs
  • Expert Collaboration: Collaborate with other location experts to leverage expertise to solve the client’s business problems
  • Team Mentorship: Mentor and coach junior team members on client communication, project management, analytics best practices, and relevant methodologies

7. Analytics Engineer Job Description

  • Data Taxonomy: Add additional data, maintaining an organized, documented and well-designed taxonomy for user-facing tables
  • Engineering Practices: Apply engineering best practices to the data transformation layer
  • SQL Optimization: Improve the efficiency of the most demanding transformation queries with performant, clean SQL
  • Operational Analytics: Enable operational analytics by syncing data to 3rd party tools, "closing the loop" in data circulation
  • Self-Service Enablement: Be the keystone for self-service analytics and data visualization
  • Tool Management: Manage data visualization tooling
  • Dashboard Ownership: Build and own mission-critical dashboards
  • Data Training: Support the organization to answer questions with data through training, tooling, process and ingenuity
  • BI Development: Contribute to the development of a driver-facing business intelligence tool
  • ML Collaboration: Collaborate with software engineers to meet data requirements for machine learning pipelines
  • Project Flexibility: Work on additional projects based on experience and interest

8. Web Analytics Intern Overview

  • Data Extraction: Extract data from multiple sources (Google Analytics, CMS and SAP)
  • Insight Generation: Transform raw data into actionable business insights and dashboards
  • SEO Optimization: Work with the Web Analytics Manager to make SEO changes to improve Organic traffic
  • Performance Reporting: Deliver daily and weekly performance updates as well as work on ad hoc data
  • Channel Evaluation: Evaluate the performance of acquisitions, Organic, Paid, Affiliate and others
  • Dashboard Development: Develop and manage web-based reporting and dashboards, such as Data Studio
  • CMS Support: Support the web team and or marketing team with CMS updates
  • UAT Assistance: Assist with monthly user acceptance testing and new website releases
  • Search Management: Maintain website search results to provide the correct product results
  • Business Alignment: Understand business needs and objectives
  • Industry Awareness: Keep up to date with industry news and trends

9. Analytics Manager Details and Accountabilities

  • Project Management: Manages analytic projects, including profitability, timeliness, quality, and client value
  • Analytical Communication: Communicates complex analytical results and corresponding implications to both internal and external clients in a manner that will be easily understood
  • Storytelling Presentation: Creates compelling presentations to tell the analytic story, demonstrating value by providing actionable insights with recommendations
  • Needs Assessment: Proactively identifies business needs and develops actionable project plans to serve them
  • Client Engagement: Serves as primary contact on all phases of the analytic project from problem definition through presentation, appropriately managing client expectations throughout the project
  • Team Collaboration: Collaborates with peer managers to effectively manage team resources to produce high-quality deliverables
  • Efficiency Improvement: Continuously focuses on ways to improve efficiencies and quality control within the group
  • Progress Communication: Navigates, understands, and communicates the progress of projects conducted at all levels of the team
  • System Optimization: Identifies and seeks improvement for current systems/methodologies, and applies industry techniques/ideas/trends
  • Talent Development: Selects, develops and evaluates personnel, ensuring efficient operation of the function
  • Technical Leadership: Provides technical leadership in the organization

10. Analytics Manager Tasks

  • Industry Understanding: Develop a solid understanding of the pharmaceutical landscape and the business
  • Team Leadership: Lead a team of Analysts that provides technical insights and trend analysis to the commercial teams, defining the estimated financial impact of such decisions
  • Internal Consulting: Act as a consultant to the Marketing, Sales, Trade and Access Teams
  • Commercial Insights: Provide insights by leveraging knowledge of the commercial landscape, monitoring business trends, and performance to forecast
  • Strategic Development: Participate in the strategic development of analytic and technical resources
  • Market Support: Support business relationships related to existing and new products and markets
  • Payer Analytics: Lead key payer analytics initiatives such as payer segmentation, forecasting and revenue risk assessment, and optimization
  • BI Initiatives: Lead key Business Intelligence initiatives such as program evaluation, forecasting, revenue risk assessment, and optimization
  • Solution Architecture: Work with Analysts, functional leaders and subject matter experts to understand current and future data analysis goals and architect solutions to meet those goals
  • Cross-Functional Collaboration: Collaborate with internal teams, alliance partners, and vendors to coordinate cross-functional analysis and data acquisition
  • Ad-Hoc Analysis: Support the Analyst team with responding to ad-hoc queries and data-mined analyses about market opportunities
  • Data Enablement: Proactively identify additional data sources, tools, and requirements for the business
  • Compliance Focus: Maintain a compliant mindset to ensure all operational tasks are compliant and that appropriate analyses are performed to evaluate performance
Relevant Information
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What Does An Analytics Manager Do?
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