Kaylea Haynes

Data Scientist


Hello World

Hi I’m Kaylea, a Manchester based data scientist currently working at Residently. I’ve done quite a lot of work in time-series analysis, demand forecasting and changepoint detection. I’m currently broadening my skills working on different projects.

The plan for this blog is to:

  • share my knowledge on time-series analysis and forecasting, particularly applied in industry
  • document my learnings as I grow and develop as a data scientist
  • share any thoughts and discussions from attending data science meet-ups.

Feel free to contact me about anything in this blog via LinkedIn or Twitter.


Recent Posts

Starting a new job remotely

I am writing this blog post 4 weeks into a new job, all of which has been during the Covid 19 lockdown. Here are some tips.

Academia to Tech

Introduction When Rachael from Her+ Data Manchester got in contact asking if I would be a speaker at one of their events this year she …

Learning python as an R user

Introduction As an avid listener to some tech podcasts, particularly ones that are run or feature people that I know, (pydataMCR and …

Changepoint Detection

Happy New Year (although by the time this post goes live it’ll be halfway through January, so it’s probably becoming a bit too late to …

I've started my chRistmas countdown

I had this grand idea last year of making an R advent calendar, although I was a bit too late to make one on time for the Christmas …

Speaker Events

Fun with Functions

On the 4th of February I presented a workshop on functions in R at the R Ladies Manchester meetup.

Publications and Resources

PyDataMCR Podcast Episode 3 - Forecasting Ft. Kaylea Haynes

I joined the team at PyDataMCR on their podcast to talk about forecasting.







Data Scientist


May 2020 – Present Manchester

Data Scientist


Apr 2017 – Apr 2020 Manchester
Projects include:

  • Demand forecasting to get the right stock in the right place at the right time.
  • Optimising pick runs in a warehouse.


STOR-i Lancaster University

Sep 2012 – Oct 2016 Lancaster
Detecting Changes in Big Data