Mark Farragher, Statistical Methods Developer in Cambridge, United Kingdom
Mark Farragher

Statistical Methods Developer in Cambridge, United Kingdom

Member since April 17, 2020
Mark is a highly analytical data scientist and open-source developer who most recently worked in a startup environment. He trained as an economist and specializes in statistical modeling, causal inference, and experimentation. He has a breadth of experience, having worked in contracting and employment on data projects for public, private, and third-sector clients. He is an excellent communicator who often gives talks at conferences and writes blog posts on data topics.
Mark is now available for hire

Portfolio

Experience

Location

Cambridge, United Kingdom

Availability

Part-time

Preferred Environment

Google Cloud Platform (GCP), NumPy, Pandas, Linux, MacOS, Windows, STATA, Tableau, Looker, Git, BigQuery, SQL, Python

The most amazing...

...personal project I've worked on is an open-source econometrics library for Python called Appelpy. It reached over 120 stargazers on GitHub.

Employment

  • Data Scientist

    2020 - PRESENT
    Boutique Health Consultancy (Contract)
    • Developed scalable analytics tools on a healthcare data project for a boutique healthcare consultancy’s analytics team. Led on software engineering and ETL intensive tasks.
    • Moved Python code away from notebooks, with some refactoring, into a more robust system; I have introduced best practices in software engineering, e.g., logging, unit testing, or modularization of code.
    • Developed ETL pipelines with Parquet files and analytics tools to reduce the team’s time spent on ad-hoc requests, with a long-term view of making the analytics more self-serve for the client.
    • Automated the generation and sending of data outputs, e.g., with Microsoft Teams Flows or BAT scheduling.
    • Automated advanced Excel outputs, with a mix of Python libraries such as Xlwings or Openpyxl.
    Technologies: Bayesian Statistics, Causal Inference, Data Analysis, Statistical Methods, Windows, Microsoft Excel, Pandas, Scrum, Agile, Python, Machine Learning, Tableau, Test-driven Development (TDD), Excel VBA, Parquet
  • Data Scientist

    2018 - 2020
    Triptease
    • Developed logic for systematically managing hotels' online presence on metasearch advertising channels, harnessing their unique characteristics and multiple data sources. Helped to launch the MVP and iterate logic once we had more customers.
    • Built dashboards and tooling to help our cross-functional squad monitor the health of the metasearch product; e.g., anomaly detection system, integration health, or model and product performance.
    • Developed internal Python libraries to analyze our data more robustly and systematically. Automated dozens of my common analytics tasks and modeling workflow.
    • Delivered a talk at PyData London 2019 conference on the applications of causal inference to hotel websites.
    • Undertook research that influenced the sales process (e.g., new "guard rails"), budget optimization, and models tailored to hoteliers' different objectives (e.g., whether to optimize acquisition or the return on ad spend).
    • Upskilled and onboarded new colleagues, such as data analysts, on parts of our tech stack.
    • Undertook the largest A/B test of on-site messaging across thousands of hotel websites. Wrote up the white paper on the test results and discussed the test in a webinar with customers.
    Technologies: Bayesian Statistics, Causal Inference, Data Analysis, Google BigQuery, Statistical Methods, Microsoft Excel, Pandas, Git, Agile, Machine Learning, SaaS, Google Cloud Platform (GCP), BigQuery, SQL, Looker, Python
  • Data Analyst

    2018 - 2018
    Triptease
    • Ran multiple A/B tests to demonstrate the value of Triptease’s products to the largest hotel groups. The rigorous process and outputs contributed to reducing client churn in Q1 2018.
    • Increased the efficiency and effectiveness of the original A/B testing process via, e.g., reporting templates, automation of tasks, or dashboard and tool development.
    • Undertook analysis and research that led to development of new product and platform features.
    • Analyzed conversational data with NLP to refine the front desk chatbot product, which led to higher accuracy.
    • Assisted in the hiring of new data scientists in H2 2018 (and eventually moved into a data science role in a new squad).
    Technologies: Bayesian Statistics, Causal Inference, Data Analysis, Google BigQuery, Statistical Methods, Microsoft Excel, Pandas, Google Cloud Platform (GCP), Git, Agile, Machine Learning, SaaS, Python, BigQuery, SQL, Looker
  • Analyst/Consultant

    2017 - 2017
    Self-employed
    • Contracted at Triptease as a data analyst for one month before moving into a permanent role.
    • Developed strategy and evidence bases for supporting the startup of new universities internationally (consultancy for Susan Jackson Associates).
    • Undertook quantitative and qualitative analysis on international higher education policy.
    Technologies: Data Analysis, Statistical Methods, Economics, Windows, Microsoft Excel, BigQuery, SQL, Looker
  • Consultant

    2015 - 2017
    Public and Corporate Economic Consultants (PACEC)
    • Authored a publication on England's knowledge exchange (KE) policy and developed a database tool for monitoring universities' KE strategies as part of one of our largest consultancy projects (£100,000+). I wrote the proposal.
    • Wrote the baseline evaluation report for the Newton Fund, a £735 million fund to develop UK research partnerships in 15 countries. Developed the quantitative analysis methodology and became an SME on international research partnerships.
    • Authored dozens of pieces of research on economic policy and higher education policy for clients at different levels of government, e.g., UK central government, local authorities, local enterprise partnerships, public-private consortia, etc.
    • Introduced and applied new technology to our analytics, e.g., use of Tableau.
    Technologies: Data Analysis, Statistical Methods, Economics, Windows, STATA, Tableau, Microsoft Excel

Experience

  • The State of the English University Knowledge Exchange Landscape
    https://dera.ioe.ac.uk/29698/

    Client: Higher Education Funding Council for England (HEFCE).
    I was one of the main authors of this publication, and the wider project was one of the largest contracts (in terms of revenue) that the business had secured. The web link above has the full report, so that may be useful for context. Findings from previous PACEC reports on knowledge exchange have been used in the HE sector at workshops and conferences, especially by policymakers, so it is likely to be the same for this report over the next few years.

  • Appelpy (Applied Econometrics Library for Python)
    https://github.com/mfarragher/appelpy

    I am the developer of the Applied Econometrics Library for Python (Appelpy). It seeks to bridge the gap between the software options that have a simple syntax (such as Stata) and other powerful options that use Python's object-oriented programming as part of data modeling workflows.
    It has been a personal project I worked on over some weekends and evenings. I marketed the project and it became one of the most-starred projects on regression modeling on GitHub.

  • Newton Fund Baseline Evaluation
    https://www.newtonfund.ac.uk/about/newton-fund-evaluation/

    Clients: the UK's BEIS and DFID government departments.
    I undertook quantitative analysis and desk research to develop the baseline evaluation for the Newton Fund by drawing upon international and national literature and datasets encompassing innovation policy. I authored 15 country-level reports that assessed the innovation capacity of the partner countries and the high-level report.

Skills

  • Languages

    Python, SQL, Excel VBA
  • Libraries/APIs

    Pandas, Scikit-learn, NumPy
  • Tools

    Looker, Git, Tableau, STATA, BigQuery, Microsoft Excel
  • Paradigms

    Agile, Scrum, Test-driven Development (TDD)
  • Other

    Google BigQuery, Consulting, Economics, Machine Learning, Statistical Methods, Causal Inference, SaaS, Data Analysis, A/B Testing, Bayesian Statistics, Parquet
  • Platforms

    Google Cloud Platform (GCP), Windows, MacOS, Linux
  • Industry Expertise

    Project Management

Education

  • Bachelor of Science degree in Economics
    2012 - 2015
    London School of Economics & Political Science - London, United Kingdom

Certifications

  • Chartered Statistician
    OCTOBER 2020 - PRESENT
    Royal Statistical Society

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