Oliver Laslett, Machine Learning Developer in London, United Kingdom
Oliver Laslett

Machine Learning Developer in London, United Kingdom

Member since November 27, 2019
Oliver is a full-stack data scientist with experience delivering end-to-end data products using NLP, Bayesian methods, and predictive analytics. Oliver helped scale an AI Insuretech from seed round to recent Series B at £25 million. He has experience consulting with a wide range of enterprise clients in insurance, financial services, aerospace, and defense.
Oliver is now available for hire

Portfolio

  • Freelance
    SQL, Tableau, Looker, ETL, DataViz, Analytics, Data Analytics...
  • Cytora
    Amazon Web Services (AWS), JavaScript, Flask, AWS...

Experience

Location

London, United Kingdom

Availability

Part-time

Preferred Environment

Git, VS Code, Vim Text Editor, MacOS, Linux

The most amazing...

...data discovery I have made is computing the distance between the walls of every set of neighboring buildings in the whole UK.

Employment

  • Data Scientist

    2019 - 2020
    Freelance
    • Developed a new open-source BI tool for the modern data stack - github.com/lightdash/lightdash.
    • Implemented product analytics tracking, data transformation, and dashboards for leading an edutech startup in the UK. In charge of statistics that were reported in national news and to the cabinet office.
    • Designed and implemented a completely new credit scoring system for a large African bank responsible for millions of dollars in personal loans.
    Technologies: SQL, Tableau, Looker, ETL, DataViz, Analytics, Data Analytics, Google Cloud Platform (GCP), AWS, Databases, Scraping, Google Data Studio
  • Machine Learning Scientist

    2015 - 2019
    Cytora
    • Built NLP and geospatial data pipelines to power machine learning for risk analytics products covering 23 million buildings in the UK.
    • Designed an explainable AI toolbox to increase customer adoption of predictive models, now generating $1.5+ million ARR.
    • Delivered machine-learning predictions as a suite of 15 APIs built on Kubernetes.
    • Managed crowd-sourced labeling operation with >100 labelers. Built internal monitoring platform to measure labeler quality.
    • Built a backtesting framework to measure the performance of risk pricing models responsible for >$500 million in revenue.
    Technologies: Amazon Web Services (AWS), JavaScript, Flask, AWS, Google Cloud Platform (GCP), PyMC, Scikit-learn, NumPy, Pandas, Go, Python

Experience

  • Lightdash - Open Source BI
    http://GitHub.com/lightdash/lightdash

    An open-source alternative to BI tools such as Looker, with a semantic layer. Allows data analysts to build data models in the tools they love and non-technical users explore data with an easy-to-use low-code interface.

  • Detecting Clickbait in News Articles
    https://www.youtube.com/watch?v=NfaHA17CxrI&t=1s

    An NLP pipeline to ingest a news feed API and classify news articles as clickbait or not. Presented as a workshop at PyData 2017.

  • Bayesian Model of Fairness, Bias-Detection.
    https://www.youtube.com/watch?v=tX5YDf42DnY&t=4s

    Built a hierarchical Bayesian model to detect bias in open-source police stop-and-search data. Results were presented at a conference.

  • Jupyter Notebook Testing Framework (nbval)
    https://github.com/computationalmodelling/nbval

    An extension to test Jupyter notebooks. The project helps to keep Jupyter notebooks up to date and free of errors. The project is open-source with over 240 stars on GitHub.

Skills

  • Languages

    Python 2, Python 3, Python, JavaScript, C, SQL, JavaScript 6, TypeScript, Go, C++, C++11
  • Frameworks

    Flask, Spark, Express.js
  • Libraries/APIs

    Flask-RESTful, SpaCy, NumPy, Pandas, React, Scikit-learn, PyMC, TensorFlow, Node.js
  • Tools

    BigQuery, Apache Beam, Seaborn, DataViz, Vim Text Editor, VS Code, Git, Tableau, Looker
  • Platforms

    Google Cloud Platform (GCP), Linux, MacOS, Amazon Web Services (AWS)
  • Other

    Machine Learning, Statistics, Bayesian Statistics, Bayesian Inference & Modeling, Data Analytics, Classification, Regression, Data Mining, Generalized Linear Model (GLM), Support Vector Machines (SVM), Probabilistic Graphical Models, Stochastic Modeling, Stochastic Differential Equations, Google BigQuery, Technical Leadership, Neural Networks, Natural Language Processing (NLP), Data Engineering, Full-stack, Text Mining, Graphical Models, Agile Data Science, Deep Learning, Convolutional Neural Networks, Analytics, AWS, Scraping, Google Data Studio
  • Paradigms

    Functional Programming, ETL
  • Storage

    Elasticsearch, Databases

Education

  • Ph.D. in Physics
    2013 - 2017
    University of Southampton - UK
  • Master's Degree in Aerospace Engineering
    2009 - 2013
    University of Sheffield - UK

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