Hey there, I am

Victor Johnson

Data Scientist / AI Engineer | Production RAG & LLM Systems | Data Science, AI, ML | Azure, Python

Data Scientist / AI Engineer with 7+ years in ML/data and 2+ years specializing in production LLM/GenAI systems, including RAG, intelligent search, and LLM-powered applications in Azure.
I own LLM systems end-to-end: ingestion, embeddings, retrieval, prompt orchestration, evaluation, deployment, and monitoring - focused on reliability, performance, and cost in real products.
Core: LLMs, RAG, vector search, LLM evaluation, Python, Azure OpenAI, Spark, MLOps, etc.

England, United Kingdom

LinkedIn GitHub

Tech Stack

LLMs & Generative AI

Large Language Models (LLMs)
Generative AI
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Semantic Search
Embeddings & Vector Search
Vector Databases
LLM Evaluation & Monitoring
LLMOps
Chatbot Development
LlamaIndex
Azure OpenAI
Azure AI Foundry

Machine Learning & NLP

Machine Learning
Applied Machine Learning
Natural Language Processing (NLP)
Scikit-learn
Artificial Intelligence (AI)
Predictive Maintenance

Data Science & Analytics

Data Science
Python
SQL
Transact-SQL (T-SQL)
Statistical Modeling
Data Visualization
Financial Modeling

Data Engineering & Big Data

Apache Spark
Azure Databricks
Apache Kafka
Kafka Streams
Apache Airflow
Azure Data Factory
Elasticsearch
Azure SQL

Knowledge Graphs & Search

Knowledge Graphs
Knowledge Graph Data Engineering
Semantic Search & Information Retrieval

MLOps & Production AI

MLOps
MLflow
Model Monitoring
Model Drift & Bias Detection
Docker

Cloud & Platforms

Microsoft Azure
Azure Machine Learning
Oracle Cloud Infrastructure (AI Foundations)

Software & APIs

FastAPI
REST APIs
Software Development
Git
GitHub

Experience

Data Scientist (AI/LLM Focus)

Feb 2021 — Present

Company - SYMEUS LTD

England, United Kingdom · Hybrid | Industry - Finance

GenAI & LLM Systems (Primary): Led end-to-end design and production deployment of LLM, RAG, and Agentic AI systems, covering ingestion, embedding pipelines, retrieval, orchestration, simulation, evaluation, deployment, and monitoring - reducing manual effort by ~50% Built LLM-powered search, chatbots, and ranking workflows used in live products. Designed evaluation frameworks (precision/recall, F1, BLEU/ROUGE, relevance, faithfulness) to reduce hallucinations and improve grounding. Implemented prompt engineering, guardrails, output validation, and LoRA-based adaptation for domain-specific reliability and performance. Ran structured A/B testing across models, embeddings, retrievers, and prompts to optimize quality, latency, and cost. Contributed to DevOps and CI/CD workflows for deploying and monitoring GenAI / LLM solutions in production, supporting versioning, testing, and release automation. Machine Learning & Applied Analytics (Secondary): Developed forecasting and statistical models for revenue, traffic, and user activity using Python and ML frameworks. Implemented Monte Carlo simulations for scenario planning and risk modelling, improving forecast robustness and reducing manual sensitivity analysis time by ~30%. Built automated analytics pipelines integrating GA4, GSC, and internal datasets. Data Engineering, Platform & DevOps: Designed scalable ETL and data pipelines (Spark, Azure Synapse) supporting ML and near real-time analytics. Optimized complex SQL/T-SQL workloads and built KPI dashboards (Power BI, Streamlit). Strengthened data governance and validation, reducing reporting turnaround time by ~40%. Contributed to DevOps and CI/CD workflows for deploying and monitoring GenAI / LLM solutions in production, supporting versioning, testing, and release automation.

Data Scientist (ML Focus)

Dec 2018 — Dec 2020

Company - Alstom

Bengaluru, India · On-site | Industry - Railways

Applied Machine Learning & Predictive Systems: Developed production machine learning models for predictive maintenance, including Remaining Useful Life (RUL) estimation for critical train components Built time-series and survival analysis models to predict failures, degradation, and maintenance needs across multiple subsystems Analyzed high-volume telemetry data to identify failure patterns, sensor drift, and anomalous behavior in operational environments Designed component-level health indicators and engineered features that improved prediction accuracy and model stability Applied Monte Carlo simulations to model failure uncertainty and maintenance scheduling scenarios, improving preventive maintenance planning and reducing unplanned downtime risk while accelerating decision analysis cycles. Data Engineering & Model Integration Implemented robust data validation, preprocessing, and feature pipelines to ensure reliability of sensor and operational data Integrated predictive models into operational reporting and decision-support systems, enabling faster and more informed maintenance decisions Supported condition-based maintenance strategies that improved fleet availability and reduced unplanned downtime Analytics Platforms & Visualization Built dashboards in Shiny, Qlik Sense, and Tableau to visualize asset health, predictions, and maintenance KPIs Contributed to the setup of the operations center by delivering KPI-driven visualizations and automated model outputs Applied IEC 62541 standards to improve data acquisition consistency and interoperability across systems

Junior Data Scientist

Dec 2017 — Dec 2018

Company - Alstom

Bengaluru, India · On-site | Industry - Railways

Developed an Elasticsearch-based search application leveraging BM25 relevance scoring, inverted indexes, and NLP techniques for information retrieval. Developed automated ETL pipelines using Apache Airflow Contributed to Spark and Kafka streaming workflows for real-time telemetry data processing Built RPA workflows to automate SAP-based maintenance data handling

Data Science Intern

Sep 2017 — Nov 2017

Company - Pi Revolutions

Bengaluru, India · On-site | Industry - Retail Tech

Supported data analysis and automation workflows for NFC-enabled billing kiosks Performed exploratory analysis to support process improvements

Intern

Aug 2016 — Sep 2016

Company - Alstom

Bengaluru, India · On-site | Industry - Railways

Automated routine business processes using VBA in Excel, ensuring compliance with internal data standards and improving efficiency, which saved more than 10 hours of reporting work each week