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Experienced Data Scientist/Machine Learning Engineer
Laurence Day
,
Manchester, United Kingdom
Experience
Other titles
Skills
I'm offering
I am enthusiastic about Machine Learning/AI and Data Science. I enjoy working collaboratively, finding the simplest solutions to difficult problems. I have built and deployed multiple highly successful models in production environments in Financial Services and E-commerce
Projects include:
- Recommender Systems
- Credit Scorecard
- Prime prediction
- Customer Intent modelling
- Marketing optimisation
Favourite Tools
- Python (Pandas, sklearn)
- Deep Learning (Pytorch, Keras)
- GBDTs (XGBoost, CatBoost, LightGBM)
- Azure, AWS, GCP
- Terraform
- GitHub Actions
- PowerBI
1st Class Hons MPhys Physics with Astrophysics and Cosmology focused in Astrophysics from Lancaster University
Projects include:
- Recommender Systems
- Credit Scorecard
- Prime prediction
- Customer Intent modelling
- Marketing optimisation
Favourite Tools
- Python (Pandas, sklearn)
- Deep Learning (Pytorch, Keras)
- GBDTs (XGBoost, CatBoost, LightGBM)
- Azure, AWS, GCP
- Terraform
- GitHub Actions
- PowerBI
1st Class Hons MPhys Physics with Astrophysics and Cosmology focused in Astrophysics from Lancaster University
Markets
United Kingdom
Links for more
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Industries
Language
English
Fluently
Ready for
Ongoing relation / part-time
Available
My experience
2019 - ?
job
Machine Learning Engineer
CatBoost, XGBoost.
CarFinance 247, Manchester
Use Gradient Boosting (CatBoost, XGBoost) and Neural Networks (Pytorch, Keras) to solve a diverse range of complex business problems
Automate model training, hyperparameter selection and experiments using
Cloud Platforms (GCP, Azure)
Create reliable, scalable and stable cloud infrastructure as well as manage
all model deployments by creatively combining Terraform, CI/CD with GitHub Actions, and Azure Machine Learning services
Monitor deployments with a custom logging framework and PowerBI for
visualizing performance
Collaborated with internal stakeholders, identifying, gathering and understanding complex requirements for customer, product and projects
needs
Delivery of multiple highly performing models from start to finish, bringing
significant improvement in key metrics leading to ~£millions per year
increase in profit
Utilize complex credit data, customer behavioural data, product data,
developing required domain specific knowledge for effective use
Over 1 million predictions to date with no recorded downtime
Use Gradient Boosting (CatBoost, XGBoost) and Neural Networks (Pytorch, Keras) to solve a diverse range of complex business problems
Automate model training, hyperparameter selection and experiments using
Cloud Platforms (GCP, Azure)
Create reliable, scalable and stable cloud infrastructure as well as manage
all model deployments by creatively combining Terraform, CI/CD with GitHub Actions, and Azure Machine Learning services
Monitor deployments with a custom logging framework and PowerBI for
visualizing performance
Collaborated with internal stakeholders, identifying, gathering and understanding complex requirements for customer, product and projects
needs
Delivery of multiple highly performing models from start to finish, bringing
significant improvement in key metrics leading to ~£millions per year
increase in profit
Utilize complex credit data, customer behavioural data, product data,
developing required domain specific knowledge for effective use
Over 1 million predictions to date with no recorded downtime
Machine learning, Azure, Training, Cloud, Github, Neural networks, Infrastructure, Keras, Performing, Framework, CI / CD
2018 - 2019
job
Data Scientist
Machine Learning.
The Hut Group, Manchester
Creatively engineered a novel product Recommender System for the ecommerce platform, significantly improving key performance metrics
including a 25% increase in coverage
Rapidly gained a solid understanding of the literature
Scalable deployment using Docker and Kubernetes
Pioneered the Machine Learning Journal Club, to increase collaboration and enhance knowledge within and beyond the team
THG Accelerator Graduate, studying various Machine Learning algorithms
including Clustering, NLP and Software Engineering Good Practices (SOLID etc.)
Delivered a dashboard application to monitor warehouse activity,
combining front end, back end and database knowledge
Created a Tableau dashboard to monitor Recommender System
performance on all THG websites, and target areas to improve with future
projects
Creatively engineered a novel product Recommender System for the ecommerce platform, significantly improving key performance metrics
including a 25% increase in coverage
Rapidly gained a solid understanding of the literature
Scalable deployment using Docker and Kubernetes
Pioneered the Machine Learning Journal Club, to increase collaboration and enhance knowledge within and beyond the team
THG Accelerator Graduate, studying various Machine Learning algorithms
including Clustering, NLP and Software Engineering Good Practices (SOLID etc.)
Delivered a dashboard application to monitor warehouse activity,
combining front end, back end and database knowledge
Created a Tableau dashboard to monitor Recommender System
performance on all THG websites, and target areas to improve with future
projects
Machine learning, Ecommerce, Docker, Websites, Deployment, Kubernetes, Database, Tableau, Software engineering, Algorithms, Engineering, NLP, SOLID, Software
My education
Stanford University
N/a, N/a
N/a, N/a
Lancaster University
MPhys, Physics
MPhys, Physics
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