Jon Howells, Developer in London, United Kingdom
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Jon Howells

Verified Expert  in Engineering

Data Scientist and Software Developer

London, United Kingdom
Toptal Member Since
May 15, 2020

Jon has been the lead data scientist one of the world's largest technology consultancies for several years, with experience managing large data science and engineering teams, and developing data strategies and product roadmaps. He has a strong leadership and communication style, and a solid academic and technical background, with an MSc in Machine Learning from University College London. He has led large, complex engagements across the education, consumer goods, retail, and public sectors.


SQL Functions, Amazon Web Services (AWS), Dataiku, Azure, Git, Docker...
Python, Machine Learning, Artificial Intelligence (AI)...
SQL Functions, SQL, Python, Data Analysis




Preferred Environment

Amazon Web Services (AWS), Python, Team Leadership, Artificial Intelligence (AI), Agile, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), GPT, PyTorch

The most amazing...

...thing I've done is lead a large team of data scientists, engineers, business analysts and testers, to develop production AI solutions used in over 20 countries.

Work Experience

Lead Data Scientist

2016 - PRESENT
  • Developed NLP solutions to understand consumer feedback and identify trends from product reviews, social media, and consumer complaints data. These solutions used GPT-3 and open source Transformer models, such as BERT using Hugging Face and PyTorch.
  • Managed a large data science and engineering team at a global consumer goods company. Set up two new data analytics teams in India, Poland, and Mexico with over 40 employees. The role involved recruitment, training, and onboarding of these teams.
  • Worked with several clients to develop their data strategies and product roadmaps and carry out data science maturity assessments.
  • Led a team to develop a machine learning solution for a large government department to prioritize and streamline complex visa applications, saving the department time, effort and money by reducing the strain on the case-working process.
  • Led the development of a new solution to monitor emerging consumer trends across multiple geographies, utilizing natural language processing and time series modeling techniques.
  • Set up a global data science community at a multinational client with over 30 analysts across ten countries.
  • Delivered a forecasting project for one of the largest fast-food restaurants in the world, forecasting menu item sales across all restaurants in the United States and using univariate and multivariate time series models, including ARIMA and AR-Net.
Technologies: SQL Functions, Amazon Web Services (AWS), Dataiku, Azure, Git, Docker, Scikit-learn, SQL, Python, Pandas, Redshift, Python 3, Data Pipelines, Data Science, Predictive Analytics, Data Analytics, Forecasting, Predictive Modeling, Algorithms, Recommendation Systems, Data Visualization, Language Models, Deep Learning, Text Generation, Speech Recognition, APIs, TensorFlow, OpenNLP, Large Language Model (LLM), JavaScript, Chatbots

Senior Data Scientist

2016 - 2019
  • Led the development of a public relations alerting system using natural language processing and time series analysis techniques to alert the leadership for some of the world's largest consumer brands.
  • Managed team-building, industrialized NLP tools for hundreds of users at a large consumer brand company.
  • Supervised a team developing data science reports and dashboards to respond to market research briefs, using social, search, and eCommerce reviews data.
Technologies: Python, Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), JavaScript

Data Analytics Consultant

2014 - 2016
  • Led team building statistical models in Python and R for a UK retail bank covering pricing optimization, customer churn, customer cross-sell, and financial investigations.
  • Analyzed interest rate swaps data and contracts as part of an investigation into LIBOR fixing.
  • Worked with KTrace, a forensic data analysis methodology used to detect anomalies in data known to indicate potential fraud and misconduct.
  • Analyzed security transactions via the stock exchange daily official list (SEDOL) numbers to identify indirect tax savings.
  • Reviewed SQL data warehousing solutions to identify customers affected by mortgage overpayment, mortgage underpayment, and deceased customers.
  • Worked with the National Health Service regulating body Monitor to assess models on patient service costs.
Technologies: SQL Functions, SQL, Python, Data Analysis

Data Scientist

2014 - 2014
  • Developed machine learning models to predict new property sales using a range of internal and external data for a SaaS company in the proptech sector. The company was acquired by the UK's largest property website RightMove.
  • Created a web application presenting custom analytics around employee health tracking.
  • Analyzed a large client email database for a real estate company using natural language processing.
Technologies: SaaS, SQL Functions, Natural Language Toolkit (NLTK), Scikit-learn, Python

A Dash application to explore the COVID-19 open research dataset (CORD-19) using natural language processing.
Deployed as a Dash app using Docker on AWS Elastic Container Service (ECS) using AWS FARGATE.

Consumer Trends Monitoring

Led a team to develop and deploy a solution to identify consumer trends for one of the largest consumer goods companies.

The data product harnessed social data and search data using natural language processing and time series analysis to identify emerging consumer trends.

The solution covered multiple geographies and languages, including the US, UK, Japan, Brazil, Argentina, Thailand, and South Africa, alongside multiple verticals, including personal care, foods and refreshments, and home care.

This was used to inform new product development and product enhancement. As a result of the insights, a number of new products were developed or enhanced for some of the largest consumer goods brands (e.g., Dove, Magnum, Ben & Jerry's).

Public Relations Alert System

Led the development of a PR alert system for one of the world's largest consumer goods companies, Unilever. This involved developing a flow in Dataiku DSS to ingest social media, news, and reviews data, then use natural language processing and time series analysis techniques to detect negative sentiment changes towards the companies' brands or topics that the company wanted to track, such as sustainability. When PR issues were detected, the system alerted relevant leadership via Twilio so that they could coordinate a response.


Python, Python 3, SQL, JavaScript, Snowflake, TypeScript


Pandas, SciPy, OpenNLP, PyTorch, TensorFlow, Scikit-learn, NumPy, PySpark, Spark ML, SpaCy, Natural Language Toolkit (NLTK), Keras


Data Science, Agile


Dataiku, Kubernetes, Google Cloud Platform (GCP), Amazon Web Services (AWS), Azure, Docker


PostgreSQL, Data Pipelines, SQL Functions, Redshift


Data, Big Data, Text Analytics, Data Preprocessing, Machine Learning, Forecasting, Modeling, Data Analysis, Regression Modeling, Statistical Analysis, Consumer Products, Analytics, Leadership, Planning, Business Technology, Data Analytics, Predictive Modeling, Language Models, Deep Learning, Algorithms, Generative Pre-trained Transformer 3 (GPT-3), Hugging Face, Text Generation, APIs, Large Language Model (LLM), ChatGPT, OpenAI GPT-4 API, Artificial Intelligence (AI), Natural Language Processing (NLP), SaaS, CTO, Team Leadership, Solution Architecture, Custom BERT, Statistics, Computer Vision, Statistical Modeling, Data Visualization, Predictive Analytics, Text Recognition, Object Detection, Fine-tuning, DeepSpeed, Neural Networks, Speech Recognition, Chatbots, GPT, Generative Pre-trained Transformers (GPT), Back-end Development, Claude AI, Recommendation Systems, Computational Statistics, Physics, Causal Inference



Industry Expertise

Project Management


Jira, Microsoft Power BI, Git

2013 - 2014

Master of Science Degree in Computational Statistics and Machine Learning

University College London - London, UK

2009 - 2013

Master of Science Degree in Physics

Imperial College London - London, UK


Natural Language Processing Specialisation


AWS Machine Learning Specialisation

Amazon Web Services


AWS Certified Cloud Practitioner

Amazon Web Services


Dataiku Certification