Bastien Delaly

Technical Focus Areas:

• OCR: Adapting current OCR techniques for complex documents analyses

• Semantic search: Using LLM to keep context aware semantic search and remove hallucinations

• LangChain & LangGraph: Building sophisticated AI agent workflows for complex reasoning and multi-step analysis

• Neo4j & GraphRAG: Implementing knowledge graph architectures for enhanced contextual understanding

• Full-Stack AI Applications: React/TypeScript frontend with FastAPI backend, production-ready deployment

• AI Pipeline Architecture: Scalable processing systems with modern orchestration tools

Key Learning Outcomes:

→ Mastered cutting-edge AI frameworks in production environment

→ Advanced from traditional ML to Graph-based AI reasoning systems

→ Full-stack AI product development from concept to deployment

Expanded Technical Stack:

• AI/ML: LangChain, LangGraph, GraphRAG, Advanced RAG architectures

• Infrastructure: Neo4j, Docker, modern CI/CD, cloud deployment

• Development: Full-stack ownership, React, TypeScript, FastAPI

Keywords: LangChain, LangGraph, GraphRAG, Neo4j, AI Agents, FastAPI, Auth0, Full-Stack Development, Product Strategy

Key Responsibilities:

• Designed and deployed end-to-end ML pipelines using BigQuery, Cloud Run, and Docker

• Served as the technical liaison between Data, UA, and Creative Studio teams

• Developed AI systems to support user acquisition and creative performance analytics

Core Objectives:

• Reduced LTV forecast latency to enable faster UA bidding and ASO optimization

• Enhanced creative analytics using vision AI and vector search for asset tagging and duplication detection

• Surfaced early signals of competitor virality

• Automated trend scouting through multi-agent LLM chains

Notable Projects:

• Fast LTV Forecast Engine

• Vision-based creative tagging and similarity search

• Generative AI pipeline for social trend detection

• Early-alert dashboard for creative virality

Achievements:

→ New LTV model fully accepted by UA team

→ Vision-AI workflow scaled across creative teams

→ Launched internal tooling to detect and visualize emerging trends

Keywords:

Survival Analysis · LTV Forecasting · CLIP Embeddings · Vector Search · Vision AI · UA Analytics · Creative Intelligence · Generative AI · Trend Detection · Agentic Workflows

Stack:

Python, SQL, BigQuery, Cloud Run, Docker, Looker, Streamlit, GitLab, OpenAI & Gemini APIs, CrewAI, FFMPEG

Company Overview: Kovalee empowers mobile app creators. We use science and data to turn any app into a worldwide champion. We partner with app owners via the publishing model, and we bring their apps to the top charts thanks to our unique in-house tech and expertise. I witnessed Kovalee's transformation from a startup with just 5 full-time employees to a post-Series A scale-up boasting a dynamic team of 35 professionals. Key Responsibilities:

- Built the entire data environment from scratch.

- Led the data team.

- Built a comprehensive data strategy for new data products, laying the foundation for continuous improvement over the next three years, including recruitment.

- Sharing trustable data and insights. Core Objectives:

- Accurate LTV forecasting of users a day post-installation for User Acquisition and ASO optimization.

- Determining the winning variant in AB tests.

- Enhancing data visualization techniques for clearer insights.

- KPI monitoring and management.

- Serving as the primary source for data-driven insights following my analyses and recommendations.

- Architecting the entire data pipeline for optimized data flow. Notable Projects:

- Developed forecasts using advanced statistical methods like Weibull extrapolation.

- Leveraged machine learning techniques, specifically Survival Analysis, for precise forecasting.

- Implemented ETL/ELT processes to ensure data integrity and availability.

- Churn and Conversion Rate Analysis.

- User behavior analysis. Achievements: -> Successfully achieved forecast accuracy exceeding 90%, even a year into predictions. -> Cracked SKAdNetwork. Keywords: Machine Learning, Lifetime Value Predictions, Weibull Extrapolation, Survival Analysis, AB Testing, Churn Analysis, Conversion Rate Optimization, SKAdNetwork, fROAS, CPI, and Optimization. Technical Proficiency: Languages & Tools: Python, SQL, VSCode Platforms & Services: Docker, Serverless, GitHub, AWS Suite (S3, SageMaker, Lambda, Glue, Athena), Snowflake