Description

- 10 + year using data science, engineering and analytics to solve real-world problems in tech, finance and academia

- PhD in Comuter Science, MSc in Data Science

- Experienced in developing and deploying deep learning models (e.g., feed forward neural networks, graph neural networks, forecasting models etc) on cloud computing architecture

- Skilled in working with big data, geospatial data, timeseries data, relational databases and more

- Highly skilled in Python (numpy, pandas, GeoPandas, PyTorch, tensorflow, networkx), SQL, GIS, GitHub, unix

I am a qualified and experienced data scientist / data engineer. I am technically minded, but also highly personable, easy to get along with and a good communicator. I am open and honest in my working relationship and show respect to others. I can work independently and apply common and commercial sense to the work I am carrying out.

Languages

English
Native or bilingual

Workplace preferences

Can work on-site

London (up to 50km)

University of Warwick
PHD Computer Science
RESEARCH
October 2018 - Today (7 years and 8 months)
Coventry, UK
- Developed deep learning models (e.g., feed forward neural networks, graph neural networks) using PyTorch which learn complex spatio-temporal patterns in cities.

- Worked in an agile way with data engineers at Transport for West Midlands to build a cloud-based (AWS) MLOps platform to perform real-time forecasting of road networks using state of the art graph neural networks.

- Built end-to-end data processing pipelines using Python and SQL which ingest vast and messy spatio-temporal datasets and efficiently generates feature vectors.

- Assisted in West Midlands pandemic planning to help optimally locate COVID-19 vaccinations centres for the region's most clinically vulnerable.

- Lead a development team to build a web based urban analytics tool which is in use by Transport for West Midlands. The tool was built using Python, SQL, vue, and the codebase released on GitHub.

- Enhanced state of the art graph neural networks with novel data types and demonstrated their improved performance against baselines.

- Collaborated with medical school to use the methods I had developed on their datasets to analyse how people access healthcare in low and middle income countries.
Deep Learning Python Pytorch Amazon Web Services UNIX Big Data GIS SQL Git
BARCLAYCARD
Customer Targeting Manager
BANKING AND INSURANCE
December 2014 - December 2018 (4 years)
London, UK
Using SQL, SAS and Unix I was responsible for building data selection processes which drove multi-channel marketing and regulatory communications, ensuring the validity of A/B testing and providing reporting on commercial outcomes.

Major Achievements:

- Developed a targeting model in collaboration with commercial teams for a multi-channel marketing campaign in support of the launch of new product, which drove a 160\% increase in sales and 125\% increase in direct marketing response.

- Managed the transition to a new data platform for open market communications which represented significant cost savings to the business, without any negative impact on the rate and success of marketing activity.

- Automated several processes within the department, such as t-testing control segments, fraud detection tools and controls on marketing briefs.

- Managed a team of two people, ensured their development and quality of work.
SQL Data Engineer Data analysis SAS UNIX
Flypay
Internship in Software Design and Development
DIGITAL AND IT
October 2013 - December 2013 (2 months)
Developed new app features using Java for commercial-grade mobile apps.
Java Mobile application