Summary
Overview
Work history
Education
Skills
References
SELECTED PROJECTS
LEADERSHIP & BUSINESS STRENGTHS
Affiliations
Accomplishments
References
Timeline
Hi, I’m

Femi Asaolu

London,Romford
Femi Asaolu

Summary

Accomplished data and analytics professional with extensive experience in statistical analysis, data modelling, forecasting, and evidence-based decision-making within complex analytical environments.

Skilled in transforming large datasets into actionable insight using SQL, R, Python, and SAS, with growing expertise in machine learning, predictive modelling, and data science workflows. Experienced in working with structured data, feature engineering, regression analysis, classification models, and analytical problem-solving.

Proficient across a broad technical stack including SQL, Python, R, VBA, SPSS, Microsoft Power BI, Google Colab, Microsoft Office, and collaborative digital tools. Currently expanding practical capability in machine learning, AI-driven analytics, and cloud-based analytical environments through hands-on project work and continuous learning.

Recognised for strong communication, stakeholder engagement, and leadership skills, with experience translating complex analytical findings into clear presentations, reports, and business recommendations. Brings a calm, solutions-focused approach to problem-solving and thrives in project-based environments where data-driven insight supports strategic decision-making.

Overview

18
years of professional experience

Work history

HM Revenue and Customs (HMRC)
London

Corporation Tax Forecasting Analyst
2020.12 - 2026.04 (5 education.years_Label & 4 education.months_Label)

Job overview

  • Deliver updates for UK onshore corporation tax (CT) forecasts at key fiscal events (Budgets, Spring Statements, and Spending Reviews), contributing to accuracy and reliability of national economic planning.
  • Responsible for estimating impact of changes in onshore CT rates and payment schedules on tax revenues.
  • Lead model evaluation and development between fiscal events, and collaborate with OBR (Office for Budget Responsibility) in producing Forecast Evaluation Report and Model Review publications.
  • Work closely with others across Direct Business Taxes division in developing CT datasets and key modelling assumptions, as well as engaging with policy and operational colleagues across HMRC and HM Treasury (HMT).
  • Contribute to monthly receipts monitoring process, advising ONS (Office for National Statistics) and HMT on forecast-related judgments for monthly Public Sector Finances (PSF) publication.
  • Maintain regular communication with key stakeholders, including OBR, HMT, and ONS.
  • Prepare for and support critical periods, such as fiscal events by providing CT forecasts and analyses.
  • Develop and enhance Excel models, and use SAS to analyze underlying data to inform forecast assumptions.
  • Explore opportunities to automate and improve aspects of forecasting model using R.
  • Key Achievements:
  • Delivered updates on onshore corporation tax forecasts for fiscal events, including Autumn Statements and Spring Budgets from 2021 to 2024. These updates informed OBR’s Economic Fiscal Outlook publications at these events.
  • Collaborated with OBR to produce their annual Forecast Evaluation Report (FER), which assesses how UK onshore CT forecasts compare to receipts and identifies improvements for future forecasts in UK economy.
  • Developed new forecasting model for onshore CT forecast in Summer 2023, enhancing forecast robustness, efficiency, and user-friendliness of forecasting process. New model demonstrates superior accuracy compared to previous iteration, providing more reliable approach to forecasting within organization.
  • Collaborated across departments for cohesive report development.

HM Revenue and Customs (HMRC)
London

Head of Compliance Modelling (Grade 7)
2018.11 - 2020.12 (2 education.years_Label & 1 education.month_Label)

Job overview

  • Led Knowledge Analysis and Intelligence (KAI) Compliance Strategy team to support business customers in modelling impact of resource allocation changes on compliance yield.
  • Analyze estimation of benefits expected from change initiatives.
  • Discover development of tools and models to aid analysis.
  • Preparation of Budget measures for Office for Budget Responsibility’s certification.
  • Key Achievements:
  • Enabled team to simultaneously deliver high-priority budget analysis and improved Compliance Resource Allocation Model (CRAM) within scheduled timelines.
  • Facilitated delivery of revised Anti-Money Laundering Supervisory Regime (AWRS) benefits, allowing customers to advise Board about change in benefits.
  • Led analysis and modelling for introducing cash transaction limit policy to tackle evasion driven by cash.
  • Replaced old CRAM with improved version, enabling team to deliver better quality outputs faster, reduce model update time, and improve overall efficiency.
  • Collaborated with internal teams, improved overall compliance performance.

HM Revenue and Customs (HMRC)
London

Senior Tax Gaps Analyst
2017.06 - 2018.11 (1 education.year_Label & 5 education.months_Label)

Job overview

  • Act as primary contact for division and department in delivering requirements for estimating UK Tax for large businesses.
  • Provide evidence base to support consultation work on proposals to tackle non-compliance in Corporation Tax, and in VAT for Large Business.
  • Deliver improvements to large businesses tax gap methodology, to help support department’s strategy in understanding extent to which how non-compliance occurs and how causes can be addressed.
  • Key Achievements:
  • Successfully improved accuracy and reliability of tax gap estimates, contributing to more effective compliance strategies.
  • Formed and maintained professional relationships with customers and senior stakeholders across Compliance Customer Strategy to steer analytical work programme.
  • Reviewed peers' work to ensure highest quality of output,.

HM Revenue and Customs (HMRC)

Head of Compliance Modelling (Grade 7) (Temporary
2016.08 - 2017.06 (10 education.months_Label)

Job overview

  • Reviewed company practices and documents for legality assurance.
  • Evolved training programmes, enhanced staff understanding of complex regulations.
  • Coordinated investigations into alleged breaches of regulations or ethics.
  • Elevated compliance standards by implementing robust policies and procedures.
  • Adapted quickly to regulatory changes ensuring uninterrupted workflow.
  • Identified areas of non-compliance through regular monitoring activities.
  • Supervised operations, ensured adherence to laws and guidelines.
  • Managed team of compliance officers to achieve organisational goals.

HM Revenue and Customs (HMRC)
London

Statistical Analyst
2014.04 - 2017.01 (2 education.years_Label & 9 education.months_Label)

Job overview

  • Supported development of KAI, Enforcement & Compliance's analytical capability in exploiting extensive range of data sources available for operational understanding, performance measures, and use of data-driven evidence in HMRC.
  • Delivered analytical program to help Enforcement & Compliance and HMRC assess their progress, improve operations, and understand any deviations from their plans. This ensures that customer needs are balanced with HMRC's strategic and operational goals.
  • Provide evidence base to support consultation work on proposals to tackle non-compliance in hidden economy.
  • Act as first point of contact for Local Compliance Change to support their requirements for forecasting and validating change benefits of Local Compliance programmes.
  • Key Achievements:
  • Delivered National Penalty Processing System (NPPS) technical note to E&C Performance Reporting Teams on integrity of several statistical NPPS reports.
  • Produced NPPS datasets documentation and quality notes to E&C analysts to enhance understanding, and promote right use of data.
  • Delivered ONS/GSS Quality Management and Reporting Tool workshop to producers of National and Official Statistics in KAI directorate.
  • Created and delivered model for Debt Management and Banking Team, enabling HMRC to accurately forecast fees for new Taking Control of Goods legislation and achieve its Tax Gap objectives.

Department for Education (DfE)
London

Statistical Officer
2008.02 - 2011.12 (3 education.years_Label & 10 education.months_Label)

Job overview

  • Analyzed and delivered children’s education outcomes at Early Years Foundation Stage for settings and schools across England.
  • Delivery of analytical evidence for Review of Early Years Foundation Stage Profile.
  • Provided statistical advice to policy colleagues, influencing decision-making.
  • Delivery of Local Authority Target Setting model to determine LAs EYFSP PSA targets.
  • Presented findings to both statistical and non-technical audiences.
  • Key Achievements:
  • Co-authored "The Achievement of Children in Early Years Foundation Stage Profile (EYFSP)" publication.
  • Delivered Local Authority Target Setting model to determine LAs EYFSP PSA targets.
  • Worked on PowerPoint Ministerial Briefing Report that accompanies bi-annual EYFSP results.
  • Managed and developed division’s user-friendly intranet system that increased collaboration between statistical officers and policy colleagues.
  • Data-driven revision of EYFS Profile, eliminating points with little impact on KS1 outcomes, leading to more effective assessment process and policy decision-making.
  • Upheld laws and regulations within jurisdiction, ensuring compliance from all parties involved.

Education

Brunel University
Uxbridge, London

BSc from Economics and Management Hons

University overview

QA
Online

Master of Science from Artificial Intelligence (AI) Data Specialist Level 7 Apprenticeship
2025.07

University overview

Skills

  • Advanced Analytics: Proficient in SQL, Python, and R for data manipulation, statistical analysis, and insight generation
  • Machine Learning & Data Science: Developing practical experience in classification modelling, feature engineering, predictive analytics, and model evaluation
  • Data Modelling: Skilled in building analytical models to support forecasting, business insight, and decision-making
  • Statistical Analysis: Experienced in regression analysis, exploratory data analysis, hypothesis testing, and summary statistics
  • Programming & Analytical Tools: SQL, Python, R, SAS, VBA, SPSS, Microsoft Power BI, Google Colab, Microsoft Office, Microsoft Teams, and Google Workspace
  • Data Visualisation & Reporting: Skilled in presenting complex data through dashboards, reports, and stakeholder-friendly insights
  • Communication: Strong written and verbal communication skills, including presentations, reporting, and stakeholder engagement
  • Leadership & Team Management: Experience leading teams, mentoring analysts, managing projects, delivering outcomes under pressure
  • Problem Solving: Strong analytical thinking with a structured approach to resolving complex business and data challenges
  • Project-Based Working: Experienced in delivering analytical work within defined project scopes, timelines, and objectives
  • Professional Strengths: Calm under pressure, public speaking, team building, collaboration, and decision-making

References

References
Available upon request.

SELECTED PROJECTS

SELECTED PROJECTS
Forecasting & Strategic Analytics Programme, Problem: Leadership required forward-looking insight for planning and decision-making., Action: Built analytical frameworks using historical trends, performance indicators, and forecasting logic., Result: Improved visibility into future performance scenarios and supported strategic planning., Compliance Modelling & Behavioural Analysis, Problem: Large datasets made risk patterns difficult to identify consistently., Action: Applied structured modelling techniques and behavioural analysis across financial records., Result: Improved understanding of performance drivers and risk indicators., Data Governance & Reporting Improvement, Problem: Reporting inconsistencies reduced confidence in analytical outputs., Action: Introduced governance controls, validation logic, and reconciliation frameworks., Result: Increased data reliability and stakeholder trust., Executive Insight & Storytelling, Problem: Senior stakeholders needed accessible interpretation of technical findings., Action: Delivered concise reporting narratives and executive-ready insight packs., Result: Enabled faster, evidence-based decisions.

LEADERSHIP & BUSINESS STRENGTHS

LEADERSHIP & BUSINESS STRENGTHS
  • Senior stakeholder engagement and business partnering
  • Strong analytical leadership and mentoring capability
  • Proven ability to lead complex analytical initiatives
  • Strong commercial awareness and operational understanding
  • Ability to translate technical analysis into strategic decisions
  • Excellent communication across technical and business audiences

Affiliations

Affiliations
  • Chess
  • Walking
  • Swimming

Accomplishments

Accomplishments

Best Forcasters Award

References

References
References available upon request.

Timeline

QA
Master of Science from Artificial Intelligence (AI) Data Specialist Level 7 Apprenticeship
2025.07
Corporation Tax Forecasting Analyst
HM Revenue and Customs (HMRC)
2020.12 - 2026.04 (5 education.years_Label & 4 education.months_Label)
Head of Compliance Modelling (Grade 7)
HM Revenue and Customs (HMRC)
2018.11 - 2020.12 (2 education.years_Label & 1 education.month_Label)
Senior Tax Gaps Analyst
HM Revenue and Customs (HMRC)
2017.06 - 2018.11 (1 education.year_Label & 5 education.months_Label)
Head of Compliance Modelling (Grade 7) (Temporary
HM Revenue and Customs (HMRC)
2016.08 - 2017.06 (10 education.months_Label)
Statistical Analyst
HM Revenue and Customs (HMRC)
2014.04 - 2017.01 (2 education.years_Label & 9 education.months_Label)
Statistical Officer
Department for Education (DfE)
2008.02 - 2011.12 (3 education.years_Label & 10 education.months_Label)
Brunel University
BSc from Economics and Management Hons
Femi Asaolu