Babatunde Odunuga


Tunde has over 13 years of experience in computing and statistical data analysis.  His key area of knowledge is Applied Statistics & Data Science.  He has experience in using advanced statistical techniques and a range of analytical tools to provide actionable insights using big data to support organisational policies, business decision making, and business transformation in projects in the private sector and within government. 

He is a multilingual Statistician with experience as a Data and Research Analyst with strong investigative, modelling & forecasting, numerical and financial research skills.  He is proficient in working with complex data manipulation, managing projects in an Agile & Scrum environment, and acting in an influential capacity to support management teams in effecting positive change in a range of business contexts.  Tunde has a BSc (Hons) in Statistics and a MSc in Computer Science.

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An initial 30 minutes consultation (face-to-face or teleconference) with Tunde will explore your specific business needs, scope the extent of your requirements, and provide an indication of the next steps that your business needs to take to harness the power of data.

Areas of Knowledge
  • Data Science – techniques & application

  • Applying Data Analytics & Data Assimilation techniques to complex and high-dimensional data

  • Marketing Analytics – customer/buyer behaviour

  • Business Intelligence techniques

  • Data: predictive analytics - forecasting, modelling and tracking user behaviour to enhance competitiveness, evaluating and analysing complex customer data for planning, profiling, segmentation, propensity and decision-making

  • Machine learning (supervised/unsupervised)

Tools & Skillset
  • Github

  • Hadoop

  • Python

  • R

  • SAS (Base, Enterprise Guide, Forecast Studio Server), Spark, R Studio

  • SQL Server, SQL, T-Transact

  • Visual Basic Studio

  • Power BI, Tableau, QlikView


  • SVN, Principal Component Analysis (PCA)

  • Clustering (K-means algorithms, decision-tree)

  • Deep Learning

  • Text Analytics

  • Hypothesis Testing

  • Predictive Modelling, Time Series Modelling, Forecasting

  • Data Mining

  • Regression Analysis – e.g. Linear, Multiple and Logistic regression modelling 

Recent Project Experience
  • Extensive experience as a Statistician with the Ministry of Justice, Welsh Government and HMRC

  • Advanced statistical techniques, machine learning & data science - private sector and within government 

  • Strategic roadmap for Census 2021 for the Office for National Statistics (ONS)

  • Development of a knowledge management tool and reporting facility to allow businesses to predict their business trends and sales forecasts

  • Information Systems & big data analytics and strategic design research – development of business solutions for Small & Medium Enterprises (SMEs)

  • Development of a usability testing research tool for investigating Human Computer Interactions (HCI) of mobile keypad and touch screen use by older adults

  • Development of a research methodology for the analysis of big data challenges in neuroscience using innovative approaches in data assimilation and inverse problem techniques (work in progress)

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