Alex Spanos, Developer in London, United Kingdom
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Alex Spanos

Bio

Alexios is a data science leader with proven line management and senior IC experience. He was most recently head of data and AI at a seed-stage startup. Alexios has built and scaled data organisations from the ground up across two high-growth companies. He is experienced in C-level stakeholder management, has executed data strategies, and delivered data science capabilities for flagship data products.

Portfolio

Wagestream
Snowflake, Python, AI Agents, Data Build Tool (dbt)
Lunos
Data Build Tool (dbt), Vercel, Supabase, TypeScript, Python, Pandas, Jupyter...
Tarabut Gateway
Python, Amazon Web Services (AWS), Data Science, Pandas, Jupyter, Data Analysis...

Experience

  • Statistics - 20 years
  • Data Science - 15 years
  • Python - 10 years
  • Machine Learning - 8 years
  • Amazon Web Services (AWS) - 5 years
  • PyCharm - 5 years
  • APIs - 4 years
  • Product Management - 3 years

Preferred Environment

Cursor AI, Amazon Web Services (AWS), Google Cloud, Kubernetes

The most amazing...

...end-to-end machine learning-powered service I've built enriched millions of financial transactions daily in real-time with actionable insights.

Work Experience

Head of Data

2025 - PRESENT
Wagestream
  • Oversaw analytics delivery for over 150 internal customers across the company. Managed data infrastructure from ingestion to the consumption layer.
  • Grew the analytics engineering team from two to five, adopting a formal hub-and-spoke model in the 1st three months at the company across two jurisdictions.
  • Negotiated vendor contract renewals worth over $0.25 million and reduced monthly data stack expenditure by 15%.
Technologies: Snowflake, Python, AI Agents, Data Build Tool (dbt)

Head of Data & AI

2025 - 2025
Lunos
  • Built a robust analytics stack with dbt and Supabase, modelling over 130 tables and implementing 1,000+ data tests; introduced data observability using Elementary and GitHub Actions for scheduled runs, alerting, and quality reporting.
  • Led the rollout of Hex as the core analytics interface, developing operational and data quality dashboards that provided the team with real-time visibility on the app's decisions.
  • Contributed to the AI decision engine by extending the TypeScript codebase, designing and delivering merchant and payer-level metrics that directly informed next-best-action recommendations.
Technologies: Data Build Tool (dbt), Vercel, Supabase, TypeScript, Python, Pandas, Jupyter, Data Analysis, Large Language Models (LLMs), Artificial Intelligence (AI), Model Context Protocol (MCP), Generative Artificial Intelligence (GenAI)

Head of Data

2021 - 2025
Tarabut Gateway
  • Delivered a 3-year data strategy by enabling data products across four cloud regions serving >150 internal users with >40 internal data products.
  • Scaled a distributed data function to 10 managers and ICs across four countries, four functional areas (data science and ML, data engineering and infrastructure, data analytics, and data asset), and two teams.
  • Architected and delivered Tarabut’s enterprise data platform using data lakehouse and data contracts principles; >80 data pipelines powering internal and external data products and analytics use cases across four jurisdictions and two cloud providers.
  • Led a successful data platform integration following strategic acquisition, reducing operational costs by around 30% while maintaining full operational continuity.
  • Developed multi-geo, generalizable, and adaptable ML-powered transaction enrichment services processing >0.5 million monthly transactions with >80% accuracy.
  • Established a group-wide data governance framework as Committee Chair, delivering full compliance with regional data protection regulations. Introduced a data quality framework and decentralized data management practices.
Technologies: Python, Amazon Web Services (AWS), Data Science, Pandas, Jupyter, Data Analysis, Natural Language Processing (NLP), Large Language Models (LLMs), Generative Artificial Intelligence (GenAI)

Lead Data Scientist

2018 - 2021
TrueLayer
  • Built new Python services and data pipelines to improve the open banking transaction classification feature and laid down the company's data science foundations as part of an autonomous 2-person team reporting to the CTO.
  • Reported to the CEO and looked after the data API as data platform product manager. Introduced the Prometheus Grafana stack with the back-end engineering team, shipped the company's first ML service, and released the first add-on feature.
  • Co-founded a new team, Insights, and served as its first product manager in addition to my data science work. Grew the team from three to seven and shipped the company's first value-add products in the data space—the income and spending APIs.
Technologies: Python, Kubernetes, Amazon Web Services (AWS), Jupyter Notebook, Data Science, Machine Learning, Product Management, APIs, Docker, PostgreSQL, Pandas, Jupyter, Data Analysis, Natural Language Processing (NLP), Large Language Models (LLMs)

Senior Data Scientist

2017 - 2018
Black Swan Data
  • Contributed to the end-to-end data science methodology within the cloud-based Spark pipeline, query optimization, in-app visualizations, and features. Collaborated with the product, engineering, and design teams using an Agile approach.
  • Designed methodology and visualization prototypes, implementing and maintaining production code for the data science component of Trendscope.
  • Introduced, evangelized, and implemented a Git-based knowledge-sharing solution for the Black Swan data science team.
  • Acted as the technical mentor for a 7-person data science team.
Technologies: Python, Amazon Web Services (AWS), Jupyter Notebook, PyCharm, Data Science, Pandas, Jupyter, Data Analysis, Natural Language Processing (NLP)

Data Scientist

2015 - 2017
IBM
  • Developed a predictive modeling component for two IBM industry solutions, Customer Insight for Banking and Customer Insight for Insurance, within the data science studio, an internal startup unit.
  • Led and participated in around 15 PoV financial services projects, from scoping to presentation. Built predictive modeling workflows using machine learning for use cases like customer churn, life events, mortgage prepayment, and asset attrition.
  • Worked with the chief solutions architect on the end-to-end pilot development of a life event prediction model for a high-profile client.
  • Was selected as a moderator for the company's worldwide new hire induction sessions with the IBM general manager.
Technologies: Python, Jupyter Notebook, R, Data Science, Pandas, Jupyter, Data Analysis

Experience

Transaction Enrichment API for Open Banking Data

https://truelayer.com/blog/transaction-classification-ai/
A Python API deployed on Kubernetes for enriching financial transaction data in real time.

I served as the data science engineer, overseeing the end-to-end data science workflow from data collection and annotation to continuous training, experiment tracking, deployment, monitoring, and all associated MLOps activities. I also used a combination of regular expressions, machine learning techniques such as named entity recognition, and NLP-based supervised learning models to accurately enrich millions of transactions daily at low latency and minimal error rates.

Education

2011 - 2012

Master's Degree in Statistics

University of Leeds - Leeds, UK

2002 - 2007

Master's Degree in Applied Mathematical and Physical Sciences

National Technical University of Athens - Athens, Greece

Certifications

NOVEMBER 2024 - PRESENT

Professional Data Engineer Certification

Google Cloud

APRIL 2021 - PRESENT

Chartered Statistician

Royal Statistical Society

FEBRUARY 2021 - FEBRUARY 2024

AWS Certified Machine Learning - Specialty

AWS

Skills

Libraries/APIs

Pandas

Tools

PyCharm, Jupyter, AWS Glue, Amazon Athena, BigQuery

Languages

Python, R, Snowflake, TypeScript

Frameworks

Streamlit

Platforms

Jupyter Notebook, Linux, Amazon Web Services (AWS), Docker, Google Cloud Platform (GCP), Kubernetes, Vercel

Paradigms

Model Context Protocol (MCP)

Storage

Data Pipelines, PostgreSQL, Amazon S3 (AWS S3), Google Cloud

Other

Statistics, Machine Learning, Data Science, Cursor AI, Large Language Models (LLMs), Data Analysis, Natural Language Processing (NLP), Big Data, Product Management, APIs, Data Build Tool (dbt), Data Engineering, Artificial Intelligence (AI), Generative Artificial Intelligence (GenAI), AI Agents, Geophysics, Supabase, Google Cloud Dataflow

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