Adam Makhlouf

Engaged to enhance data platform capabilities, and drive AI tooling adoption and AI-assisted development practices across engineering teams. - BigQuery Performance Optimization: Contributed to reduce slot usage across 100K+ daily jobs improving job completion times and reducing resource contention. - AI-assisted Development Adoption: Established Cursor + MCP server workflow as internal best practice, training dozens of engineers through hands-on sessions. Improved code quality and prevented common anti-patterns through automated guardrails integrated into development workflow. - Custom Automation Infrastructure: Developed tailored BigQuery MCP server for company-specific optimization needs, enabling engineers to automate job analysis and optimization at scale. Solution adopted across engineering teams for standardized performance improvement. - Knowledge Transfer: Led optimization workshops for 40+ engineers in data guild. Mentored team on BigQuery best practices (partitioning, clustering, query optimization) and AI-assisted development tools (Cursor, Claude Code, Codex). - Process Redesign: Simplified Analytics Engineering team's migration to dbt by proposing streamlined git workflow and modern CI/CD practices using AI-assisted development, reducing friction and improving delivery velocity.

Independent consulting practice for data engineering & AI work.

Headed data strategy and engineering, implementing a modern data stack and driving critical business initiatives in a SaaS scale-up simplifying HR and team scheduling for SMBs and their frontline teams across Europe. - Platform Architecture: Built modern data stack on GCP (BigQuery, dbt Cloud, Airbyte) within budget constraints, choosing proven technologies over expensive enterprise solutions. - Revenue Recovery: Discovered unbilled usage through systematic analysis of billing vs. actual product usage. Finding triggered complete overhaul of pricing model and billing engine, resulting in €1.5M revenue increase from existing client base over 12 months (10% of ARR). Served as technical lead for pricing system redesign. - Technical Leadership: Built and led 3-person data team while maintaining hands-on technical contribution. Mentored junior engineer and established data practices across organization. Served as technical-business bridge, translating ambiguous stakeholder needs into concrete data solutions across Sales, Customer Success, Marketing, and Finance. - Operational Improvements: Implemented automated billing system to prevent future revenue leakage and ensure fair pricing, comprehensive event tracking, and customer health scoring. Reduced manual reporting time by 10+ hours weekly for the Operations team with a BI solution based on data-team maintained assets.

Delivered various data solutions while consistently filling gaps to ensure project success. Technical Leadership: Balanced individual contribution on client projects with formal line management and project-based technical leadership of junior and mid-level consultants across multiple engagements.

Real-time micro-credit attribution for e-money retail clients in Western Africa. - Built a Machine Learning platform on Azure with banking security constraints. - Delivered a scalable and robust inferencing system that enabled real-time answer (sub-100ms) for micro-credit requests for retail clients of Orange Money (22M clients in 2022).

Set up a simple BI stack (Postgres, DSS, Tableau) but in a high security air-gapped environment.

- Architected a real-time IoT data historian solution ingesting up to 150K messages/second on AWS for a critical renewable energy infrastructure monitoring and alerting system. - Implemented the whole system using infrastructure as code with AWS CDK. - Took the additional role of product owner to fill a gap in the project team structure.

Built the company data roadmap to serve the company’s strategy. Accompanied the product team on various product and data analyses.

Data-driven investment analysis coupled with product management covering aspects ranging from operations through legal to distribution and marketing • Investment & data analysis: time-series and simple to complex systematic quantitative fund’s strategies analysis (hedge fund and long-only). • Product management: oversight of products life from inception to closure including performance, operations, and commercial activity. • Business development: product specialist role for the hedge fund products and support to the international sales team. • Designed several dashboards to monitor the full spectrum of the team’s activity (investments, sales and operations) and developed the processes to manage all data flows from our services providers feeding them. • Ad-hoc bespoke portfolio construction and optimal allocation studies for clients.

Delta-One products and options on multi-asset class underlyings, based on UBS proprietary indices and bespoke client strategies. • Priced and filled orders for the secondary market of the desk’s products. • Managed and hedged the Actively Managed Certificates in the delta-one sub-book. • Built an improved Delta spreadsheet with various additional features enabling the desk to monitor its risk more effectively. • Run reporting, price and level contribution along with various processes around the book's risk management. • Arranged transition to a more stable price contribution system resulting in reduced operational risk in our market-making commitments.

Investment Banking Division - Risk Solutions Group RSG is a global risk management house providing strategic and tactical risk solutions to help corporate clients manage their exposure to foreign exchange and interest rate volatility. • Performed modelling and Monte-Carlo simulations over a client’s liability portfolio (including bonds, floating and inflation-linked debt) to assess the effect of different hedging strategies. • Built an interest rates swap pricer to match the results obtained by the in-house one. • Prepared a daily morning update for the team and a weekly rates market update for the department also used in presentation to clients. • Improved the team’s Monte-Carlo simulation model enabling the use of a variable volatility time-structure.

• Calculated daily estimation of P&L of funds on the platform including contribution of each instrument. • Developed several tools to automate tracking of client’s positions in each share class, and producing various analysis of funds activity. • Prepared relevant data and quantitative analysis for the monthly reporting to investors in the funds of the platform. • Conducted the preliminary analysis of portfolios of potential funds to on-board on the platform to assess suitability to a specific format.

HypAM is a quantitative hedge fund project implementing a Big Data predictive algorithm to financial markets. • Designed the main process retrieving large historical data sets which then ensured data relevance and completeness. • Implemented various VBA monitoring tools to accommodate the fund’s systematic trading strategies on European Equities. • Reported and analysed the systematic strategies evolution and daily P&L of the fund.

- Data Science – Machine Learning fundamentals, Deep Learning, NLP, Computer Vision, Model Intelligibility - Engineering, DevOps & Cloud – Tools and best practices for industrialisation, deployment and model lifecycle management - Soft skills, issues & methods – Agile development, Data Organisations, Governance, AI Ethics, GDPR Tools & Frameworks - Gitlab CI, Docker, Kubernetes, MLflow, Airflow, Spark Cloud - AWS & GCP Database - SQL (Postgres) & NoSQL (MongoDB, HBase)

Preparatory years for the competitive examination to the French "Grandes Ecoles" for scientific studies.