AI Architect with 5+ years experience delivering AI solutions
🏆 Achievements
Architected a state-of-the-art cloud-based AI Platform, revolutionising the development and deployment of Generative AI capabilities in a cloud environment for Beazley.
Improved sanctions screening efficiency 90% through ML pipeline and NLP models
Reduced Loss Ratio by 13% on a ~$300M book with Behavioral Risk Pricing models
Led team of junior data scientists and engineers
Architect Machine Learning solutions for the Data Science team
Supported Data Science team to deploy ML models in production
Built relationships with stakeholders across the business to deliver outstanding solutions
Implemented MLOps pipelines and processes for governed model deployment
🚀 Projects & Startups
Starting this new company initiative called Inference Institute which is a research and development company focused on AI and Machine Learning.
I have built the GRIDSEARCH INTEGRATOR which is an online platform where online sellers upload their products and we automaticallyintegrate them into marketplaces such as Amazon, eBay, Etsy, etc.
Being part of the DataSpike.One which delivers data-driven solutions for businesses and startups.
I have also built MLCenter.orgin one week, which was suppoed to be a redisign of MLFlow, then gaveup(failfast as they say), I understood qucikly some of the patterns in MLOps are not ideal and could be improved (I might write a blog post about this).
📊 Skills Profile
Code
# Import necessary librariesimport pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport seaborn as sns# Define your scoresbusiness_score=4statistics_score=3mathematics_score=2ml_score=4dev_score=5devops_score=4management_score=3# Create a DataFrame with your skill scoresskills_data = {'Skill': ['Business', 'Statistics', 'Mathematics', 'Machine Learning', 'Software Development', 'DevOps', 'Management' ],'Score': [ business_score, statistics_score, mathematics_score, ml_score, dev_score, devops_score, management_score ]}df = pd.DataFrame(skills_data)# Define the number of skills and angles for the radar chartnum_skills =len(df)angles = np.linspace(0, 2* np.pi, num_skills, endpoint=False).tolist()# Plot radar chartplt.figure(figsize=(5, 5))ax = plt.subplot(111, polar=True)# Fill the radar chart with dataax.fill(angles, df['Score'], color='#16657A', alpha=0.7)# Add labels for each skillax.set_xticks(angles)ax.set_xticklabels(df['Skill'], size=10, fontweight='bold')ax.set_yticklabels([])# Display the radar chartplt.show()
💼 Experience
AI Architect @ Beazley Group (2024 - Present)
Architected a state-of-the-art cloud-based AI Platform, revolutionising the development and deployment of Generative AI capabilities in a cloud environment for Beazley. This governed environment not only accelerated innovation but also established robust mechanisms for measuring and analysing model output impact, significantly enhancing decision-making processes and operational efficiency.
Provided crucial AI Architecture support for cross-functional teams including Data Scientists, 3rd Party Consultants, and industry-leading vendors in the realm of Generative AI. This support ensured seamless integration of diverse expertise and technologies, contributing to cutting-edge AI solutions that addressed complex business challenges.
Orchestrated the strategic alignment of AI initiatives with the overall enterprise architecture, fostering a cohesive technological ecosystem. This alignment resulted in highly scalable solutions, future-proofing the organisation’s AI capabilities and setting the stage for sustained digital transformation.
Contributed to the cultivation and maintenance of strong, productive relationships with key technology partners, helping position the organisation at the forefront of AI innovation. These partnerships facilitated the seamless integration of cutting-edge AI solutions, accelerating the adoption of emerging technologies and maintaining a competitive edge in the rapidly evolving AI landscape.
Supported the implementation of advanced AI governance frameworks, ensuring ethical AI practices and compliance with regulatory standards. This proactive approach not only mitigated potential risks but also contributed to establishing the organization as a trusted leader in responsible AI adoption.
Senior Data Scientist @ Beazley Group (2022 - 2024)
Designing and implementing analytical pipelines and data-driven solutions
Effectively managing projects and relationships to provide outstanding customer service to stakeholders across different business lines
Managing Junior Data-Scientists and Data-Engineers workloads and career development
Aligning data ingestion and consumption within the Modern Data Architecture standards for the Data-Science team projects
Support deployment process for Dashboards and Machine-Learning solutions within Data-Science team
Designed, implemented and deployed data-driven solution for the Compliance Team, which increased the efficiency in sanctions screening by 90%
Working alongside Actuaries to re-calibrate and align Machine-Learning models with the Underwriting rationale within the business line
Designed and implemented the MLOps lifecycles and pipelines to support Data Science team deploy machine learning solutions in a governed environment
Working with 3rd Party Data-Vendors to support data acquisition and delivery process
Working with and managing workload of the 3rd Party Consultants
Data Scientist @ Beazley Group (2021 - 2022)
Supports data science lead to design analytical pipelines and solutions
Support deployment process for Dashboards and Machine-Learning based solutions within Data-Science team
Building and maintaining production Behavioural Risk Pricing models for the FSU Marine Hull business line, which reduced the Loss Ratio by 13%, and also reduced cost of service provided by the vendor
Working alongside the Modern Data Architecture team on the data ingestion pipelines for the Data-Science projects
Implemented and deployed Entity Resolution models as REST APIs to production, the service supports customer de-duplication and the ESG data-links
Implemented Named Entity Recognition APIs to support entities extraction from documents and emails, also used together with Advanced RegEx patterns to mine data from CVs
Junior Data Scientist @ Beazley Group (2020 - 2021)
Supported data science lead to design analytical pipelines and solutions
Implemented, maintained, monitored and improveed production machine learning models and solutions
Supported communication of new insights through reports, presentations and interactive dashboards
Working alongside Senior Developers I worked in a high pressure, fast-paced environment as we attempted to rebuild the back-end systems for a startup before launch.
Developing the Back-End of a Laravel application
Working with Amazon Web Services: Fargate, EBS, EC2, RDS and Serverless Lambda with NodeJS
Creating and managing a Graph API working with Prisma and GraphQL and designing the database structure
📚 Trainings & Certifications
DP-100: Designing and Implementing a Data Science Solution on Azure – Global Knowledge (Microsoft Certified Training)
Fundamentals of Data Science – Lloyds of London & University of Southampton
🎓 Education
MSc Computer Science - University of Lincoln (2018 - 2019)
Research Project
Introducing an efficient way to solve the task of Image Captioning where a machine is generating human-like descriptions for the given image and taking account of the relationship between the elements inside of the image.
Machine Learning
Learned theoretical fundamentals and practical application of machine learning algorithms. This included: supervised, unsupervised, reinforcement and evolutionary learning, proving the learned skills by solving tasks such as recognising handwritten digits and Machine Translation.
Mobile and Connected Devices
Studied cutting-edge computing concepts and in-the-field deployment of emerging Internet of Things (IoT) platforms and devices. The final project was based on creating a Smart Attendance System using technologies such as Raspberry Pi and NFC sensors, and Xamarin to develop a mobile application with a REST API to control the whole infrastructure.
BSc Computer Science (First Class) - University of Alba Iulia (2015 - 2018)
Research Project
Introducing a Stock Market Forecasting Platform where company stock data can be analysed and compared, also having a short period prediction of their stock prices.
Artificial Intelligence
Understanding the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Machine Learning and Pattern Recognition
Learning the basic fundamentals and practical application of machine learning algorithms and pattern recognition.
👨💻 About Me
Enjoy gaming, fitness, travelling and meeting new people. Former professional swimmer, powerlifter and martial artist. Passionate about graph theory and NLP
