Jamie Day

Machine Learning Engineer at Paused Perception
  • Claim this Profile
Contact Information
Location
Ryall, England, United Kingdom, GB

Topline Score

Bio

Generated by
Topline AI

0

/5.0
/ Based on 0 ratings
  • (0)
  • (0)
  • (0)
  • (0)
  • (0)

Filter reviews by:

No reviews to display There are currently no reviews available.

0

/5.0
/ Based on 0 ratings
  • (0)
  • (0)
  • (0)
  • (0)
  • (0)

Filter reviews by:

No reviews to display There are currently no reviews available.
You need to have a working account to view this content. Click here to join now

Experience

    • United Kingdom
    • Advertising Services
    • 1 - 100 Employee
    • Machine Learning Engineer
      • Aug 2022 - Present

    • Carbon Analyst
      • Jul 2021 - Oct 2021

      Maison Bengal offered me a job placement with the aim of calculating the carbon footprint of the company. After doing so, I isolated ways to reduce carbon emissions where possible. For unavoidable carbon emissions, I suggested several carbon offsetting schemes which were in line with the companies social impact. The carbon calculations were done with close reference to the up to date UK government recommendations. Maison Bengal offered me a job placement with the aim of calculating the carbon footprint of the company. After doing so, I isolated ways to reduce carbon emissions where possible. For unavoidable carbon emissions, I suggested several carbon offsetting schemes which were in line with the companies social impact. The carbon calculations were done with close reference to the up to date UK government recommendations.

    • United Kingdom
    • Environmental Services
    • 1 - 100 Employee
    • Algorithm Developer
      • Jun 2021 - Sep 2021

      I was responsible for the development of a car pooling algorithm. The algorithm could compute the best possible car pooling options for employees driving to the same office location. The aim of the algorithm was to reduce carbon emissions, save money and improve employee relationships. The programming tool that was used was python, along with the TravelTime api and Excel for input and output data storage. I was responsible for the development of a car pooling algorithm. The algorithm could compute the best possible car pooling options for employees driving to the same office location. The aim of the algorithm was to reduce carbon emissions, save money and improve employee relationships. The programming tool that was used was python, along with the TravelTime api and Excel for input and output data storage.

    • United Kingdom
    • Higher Education
    • 700 & Above Employee
    • University Teaching Assistant
      • Oct 2020 - Apr 2021

      As a Masters student I wanted to give back some of the tools and knowledge I heard learnt in the four years I have attended The University of Bristol. The best way I was aware of doing that was through teaching assistant work. One of the most valuable skills I have learnt at university is the ability to write a well structured scientific report. The ability to communicate findings in the most concise, readable and effective way is a fundamental skill any professional should have. Furthermore, the subtle intricacies of report writing can be challenging to articulate and so I knew teaching this area would hone my communications skills further. For these reasons I decided to become a teaching assistant in the Engineering Mathematics unit Mathematical and Data Modelling 2. This unit is taught to second year undergraduates and involves carrying out mathematical analysis before communicating your findings in a 15 page report. I have thoroughly enjoyed the challenge of teaching at a university level and have found giving back to the students rewarding. The experience has also given me further clarity about what defines a good report and thus has improved the quality of my own work.

    • United Kingdom
    • Food and Beverage Manufacturing
    • 1 - 100 Employee
    • Mathematical Consultant
      • Aug 2019 - Sep 2019

      I was employed to create a mathematical model to help with the drying process of long life food. Humidity and temperature sensors on the drying units provided new data every 5 seconds indicating the atmospheric conditions within the unit. On occasion, an anomaly in the system would cause the humidity or temperature to reach undesirable levels, resulting in a sub-optimal food product. Outdoorfood Limited supplied me with large amounts of sensory data from previous batches. I built a model which, for the given meal type, predicted the humidity and temperature at any given point throughout the drying process. If the live data from the drying unit deviated from this value significantly, a trigger in the system could enform management that there was a problem in the drying unit. This approach could then reduce the probability of getting an inferior finished product.

    • United Kingdom
    • Education Administration Programs
    • 1 - 100 Employee
    • Mathematics Tutor
      • Oct 2018 - Jun 2019

Education

  • University of Bristol
    Engieering Mathematics, Mathematical Modelling
    2017 - 2021
  • Thomas Hardye Sixth Form
    A levels: Mathematics, Further Mathematics, Physics, Chemistry (As level): AAAA
    2015 - 2017
  • King's College, Taunton
    GCSE: 8 A*s, inluding Mathematics, Physics and Geography, 3As
    2012 - 2015

Community

You need to have a working account to view this content. Click here to join now