Christos D

Senior Data Scientist

Consulting

Jan 2026 - Jul 2026 • 6 mos

Joined the Consultancy AI Economics Unit, which combines artificial intelligence, machine learning, and geospatial analysis with economic expertise to provide data-driven policy solutions, as a Senior Data Scientist. Led the end-to-end development and productionization of data-driven decision-support tools for government and urban planning clients. Delivered machine learning pipelines, predictive models, and analytical web platforms across cross-functional teams of data scientists, backend engineers, product managers, and UX designers. • Built an end-to-end AI-powered investor intelligence pipeline using multi-agent orchestration: integrated a Crunchbase scraping agent, a UAE presence classifier, and an LLM-based entity enrichment agent (OpenAI GPT-4o fine-tuned model), significantly reducing manual research time for high-net-worth investor profiling. • Applied Polars for high-performance data processing of CRM master datasets, implementing production-level data pipeline standards including lazy evaluation, Parquet-based storage, Git-versioned validation checklists, and modular agent-auditing workflows. • Developed a Computable General Equilibrium (CGE) model, constructing a synthetic Social Accounting Matrix (SAM) from GTAP I/O tables and calibrating trade elasticities for policy shock scenarios (oil price shocks, tariff pass-through, export adjustments), using Pyomo and IPOPT solvers for full general equilibrium. • Benchmarked LLM agents (GPT-4o and variants) across pipeline tasks for data quality, token efficiency, and output accuracy; established model evaluation standards and promoted best-in-class agentic coding practices (context files, memory banks, audit agents) across the team. • Mentored junior data scientists and engineers, proposing centralized data repositories, standardized coding pipelines, and structured PR review workflows that improved team delivery

Senior Data Scientist

Blockchain • Full-time

Aug 2024 - Jan 2025 • 5 mos

Developed AI-driven risk rating frameworks for a VC-funded Web3 startup, integrating NLP and blockchain analytics to enhance smart contract auditing and risk assessment for DeFi and stablecoin ecosystems, achieving a 30% improvement in risk rating accuracy. • Designed, trained, and deployed scalable ML models, including LSTM-based autoencoders and isolation forests for time-series forecasting, using TensorFlow, Keras, PyTorch, SciPy, scikit-learn, and Pandas, leveraging AWS SageMaker and ECS for cloud-based deployment. • Built and optimized data pipelines using advanced SQL and Python, reducing manual processing by 25% through automation and scalable solutions, with integration of AWS Glue for ETL processes. • Managed multiple concurrent data science projects, ensuring precision and alignment with business objectives in a fast-paced remote environment, while mentoring junior engineers. • Created data visualizations using Tableau and PowerBI to translate complex analytics into actionable insights for stakeholders in financial and payments ecosystems.

Data Scientist/ Scientific Project Officer

European Commission 🇪🇺

Sep 2019 - Jun 2023 • 3 yrs 9 mos

Led data science initiatives for the KCMD Data Portal and European Country Desks, designing scalable AI and distributed systems to modernize economic forecasting and analytics for financial systems, achieving a 40% reduction in processing time and 15% increase in model accuracy. • Developed and deployed machine learning models (Decision Trees, Random Forests, Neural Networks) using Python (SciPy, NumPy, PyTorch, scikit-learn, TensorFlow) and SQL for predictive modeling and statistical analysis of time-series data, with integration of AWS services for scalability. • Managed multiple data science projects, including data preprocessing, feature engineering, and ETL pipelines using SQL, Python, and AWS Glue, processing large-scale datasets from public sources with high attention to detail. • Built interactive visualization dashboards using PowerBI and Tableau to define and report metrics, driving strategic decisions in financial and economic policy contexts. • Collaborated remotely with cross-functional teams, including economists and engineers, to optimize forecasting tools and deliver data-driven solutions for financial systems.