WHAT DOES A HEAD OF ANALYTICS DO?

Published: May 6, 2025 – The Head of Analytics leads a high-performing team of Analysts and Data Scientists to deliver impactful analytical insights that drive smarter, faster decisions. This position improves analytics tooling, platform strategy, and data architecture to enable scalable, self-service analysis and low-latency insight delivery. The head of analytics also collaborates cross-functionally with internal teams to align analytical outputs with business needs and champion a data-driven culture across the organization.

A Review of Professional Skills and Functions for Head of Analytics

1. Head of Analytics Accountabilities

  • Statistical Analysis: Perform statistical analysis to design and assess the impact of changes in credit strategy in a rapidly evolving industry.
  • Consumer Behavior Analysis: Strong understanding of consumer behaviors to identify and address consumer credit risk
  • Risk Mitigation Tools: Use various tools to protect the business from credit risk-related losses
  • Strategic Alignment: Ensure credit risk management is in line with business strategy
  • Credit Environment Metrics: Put together tools, metrics to measure the current credit environment, and to identify emerging macro risks.
  • Regulatory Compliance: Ensure that credit policies are compliant with the respective country regulations.
  • Credit Strategy Development: Build and implement credit strategies for real-time, automated decision making.
  • Strategy Testing: Build, test, and monitor new credit tools and strategies from scratch
  • Stakeholder Communication: Partner with various stakeholders to ensure clear communication of regulations
  • Control and Monitoring: Ensure that adequate controls, monitoring, and testing mechanisms are in place
  • Data Analysis: Use analytical tools (e.g., SQL, R, or similar) to analyze data and problem solve with the end goal of detecting trends and making decisions.

2. Head of Analytics Job Description

  • Predictive Modeling: Generate predictive models for lighting investments based on past analysis to enable the green lighting of projects
  • Market Trend Analysis: Market trend analysis and trend scraping in social networks and the web in general
  • Content Discovery: Search for potential content that could be of interest.
  • Database Management: Take responsibility for the database search and creation
  • Algorithm Development: Create and apply algorithms to data sets
  • Data Modeling: Design data modelling processes to create algorithms and predictive models (investment fund projection models, waterfalls, IRR, internal dashboards) and perform customized analysis
  • Information Sourcing: Search or create sources of information to collaborate and support decision-making concerning projects
  • Data Visualization: Develop visualizations and create automated tools to analyse and convey data to provide clear, easy-to-read information to the team
  • Data Analysis: Analyse results, extract data, and get useful information
  • Opportunity Analysis: Analyze Estudios, past games, potential partners, and investment opportunities
  • Strategic Insight: Use this knowledge to influence the organisation's decision-making and how it addresses business challenges

3. Head of Analytics Overview

  • Business Development Planning: Lead the development and implementation of the analytics delivery business development plan
  • Performance Management: Ensure that sales targets, KPIs, and other success measures are established and communicated.
  • Profit and Loss Management: Contribute to the development of the overall Profit and Loss for data analytics with management and oversight of relevant budgets.
  • Delivery Monitoring: Monitor and report on the performance of all aspects of delivery, identify areas of concern, and take necessary actions
  • Customer Insight Collaboration: Work closely with the customer insight and development team to understand customer use and feedback
  • Stakeholder Engagement: Develop and maintain excellent relationships with senior external stakeholders, including customers, policymakers, funders, and experts in the analytics field.
  • Data Infrastructure: Create and maintain data infrastructure to support all business analysis needs.
  • Business Requirements: Specify business requirements and data needs for different functions within the company
  • Reporting and Visualization: Create and maintain business reports based on the data infrastructure and by using a visualization tool
  • Experiment Analysis: Analyze product and marketing experiments to enable optimization towards KPIs

4. Head of Analytics Tasks

  • Analytics Organization Design: Define the Analytics organization and how it will operate to add value to the Trusted mission, KPIs, operating cadence, etc.
  • Data Strategy Roadmap: Work with the Head of Business Operations to articulate a vision and roadmap for the data and analytics strategy
  • Team Building: Build a team that can analyze large, complex, and loosely defined datasets to create actionable insights
  • Analytics Process Definition: Lead the definition of how to collect the right sort of analytics, manage data privacy constraints, analyze the data, plan live data tests, and understand and interpret the results
  • Data Quality Management: Maintain consistent and high-quality data from the source system, to the warehouse, to the BI tools, to ensure accurate data along all stages of the pipeline
  • A/B Testing Standards: Develop the standards to design, execute, and evaluate A/B tests to improve the user journey
  • Internal Tools Development: Build/Buy and launch internal tools and reporting to allow all functional teams and leaders to be more data-driven in all of their decision-making
  • Insight Communication: Effectively communicate actionable data-driven insights to all audiences and influence decision makers and roadmaps
  • Predictive Modeling: Develop predictive models using econometric and statistical techniques and machine learning algorithms, to forecast customer behavior and forward-looking company performance
  • Strategic Decision Support: Efficiently strategize and aid in decision-making
  • Data Function Development: Aid in the evolution of the Data function

5. Head of Analytics Role Purpose

  • Analytical Insight Delivery: Deliver analytical insights and drive improved data-driven decision making.
  • Team Leadership: Lead and manage a team of Analysts and Data Scientists.
  • Capability Development: Assess the existing organisation structure and existing capabilities, and develop and train the team to service the business needs
  • Cross-Functional Collaboration: Work with internal teams, including commercial, product, and marketing, to deeply understand their needs in terms of provisioning the right analysis at the right time, in a consumable manner
  • Analysis Provisioning Improvement: Assess current methods of provisioning analysis and refine/improve/replace to ensure quality, scalability, and ease of self-service.
  • Tooling and Architecture Strategy: Improve company data and analytics tooling strategy, platform health, and architecture design for delivering low-latency, accurate, and deep analytical insights
  • Analytics Adoption: Focus on driving adoption and user engagement regarding Analytics tooling and outputs, decentralising Analytics, and shrinking the gap between analysis and decision-making, and action.
  • Relationship Building: Build strong relationships with Data Engineering and Business Intelligence teams, understanding their pain points/workflow, and areas where you can advise
  • Stakeholder Communication: Build effective mechanisms with key stakeholders to capture needs and communicate insights and actions.
  • Insight Communication: Communicate analytical insights effectively to the business, including to a senior audience.
  • Analytics Evangelism: Serve as a champion and internal expert across the organization for data and analytics and their use in driving smart decision-making.
Relevant Information
What Does An Analytics Lead Do?