11/04/2026 updated
GN
100 % available
AI/ML Scientist | Generative AI, Agentic Systems & Applied Statistics
Atlanta, USA
Only remote
Master of Science in Actuarial ScienceGenerative AI & NLP
Expertise in GPT-4.1, GPT-4o, Llama 2/3, LangChain, RAG pipelines, agentic AI frameworks, Model Context Protocol (MCP), Azure OpenAI & OpenAI APIs, Vertex AI Agent Builder, BERT, spaCy, Hugging Face Transformers, prompt & context engineering, and Pinecone.
Machine Learning & Deep Learning
Proficiency in XGBoost, LightGBM, CatBoost, GLMs, splines, ensembles, time-series forecasting (Prophet, ARIMA), TensorFlow, PyTorch, Keras, CNNs, RNNs, GANs, YOLO, OpenCV, SHAP interpretability, bias & fairness testing.
MLOps & Deployment
Knowledge of FastAPI, Flask, model monitoring, drift detection, responsible-AI guardrails, anomaly detection, explainability & fallback mechanisms for production-grade ML systems.
Programming & Data
Strong command of Python, R, SQL, PostgreSQL, MySQL, NoSQL, Snowflake/Snowpark, Pandas, and NumPy for data engineering and model development.
Visualisation & Business Intelligence
Experience with Tableau, Plotly, Seaborn, Matplotlib for KPI tracking and storytelling with data across diverse business domains.
Statistics & Research
Advanced skills in statistical modelling, causal inference, propensity score matching, hypothesis testing, experiment design, marketing mix models, clinical data science, and credit risk modelling.
Reinforcement Learning & Optimisation
Familiarity with reinforcement learning techniques including DQN, PPO, and A3C, as well as optimisation methods, AI ethics & fairness, and RPA using UiPath.
Credit Risk & Financial Modelling
Development of customer scorecard models for loan decisioning using ensembles and logistic regression, integrating alternative data sources to improve model precision and reduce default probability.
Clinical Data Science
Conducting statistical analyses in R for clinical trials and wound-care research, including experiment design, hypothesis testing, bias-detection, causal-inference studies, and integration of structured and unstructured EHR data.
Expertise in GPT-4.1, GPT-4o, Llama 2/3, LangChain, RAG pipelines, agentic AI frameworks, Model Context Protocol (MCP), Azure OpenAI & OpenAI APIs, Vertex AI Agent Builder, BERT, spaCy, Hugging Face Transformers, prompt & context engineering, and Pinecone.
Machine Learning & Deep Learning
Proficiency in XGBoost, LightGBM, CatBoost, GLMs, splines, ensembles, time-series forecasting (Prophet, ARIMA), TensorFlow, PyTorch, Keras, CNNs, RNNs, GANs, YOLO, OpenCV, SHAP interpretability, bias & fairness testing.
MLOps & Deployment
Knowledge of FastAPI, Flask, model monitoring, drift detection, responsible-AI guardrails, anomaly detection, explainability & fallback mechanisms for production-grade ML systems.
Programming & Data
Strong command of Python, R, SQL, PostgreSQL, MySQL, NoSQL, Snowflake/Snowpark, Pandas, and NumPy for data engineering and model development.
Visualisation & Business Intelligence
Experience with Tableau, Plotly, Seaborn, Matplotlib for KPI tracking and storytelling with data across diverse business domains.
Statistics & Research
Advanced skills in statistical modelling, causal inference, propensity score matching, hypothesis testing, experiment design, marketing mix models, clinical data science, and credit risk modelling.
Reinforcement Learning & Optimisation
Familiarity with reinforcement learning techniques including DQN, PPO, and A3C, as well as optimisation methods, AI ethics & fairness, and RPA using UiPath.
Credit Risk & Financial Modelling
Development of customer scorecard models for loan decisioning using ensembles and logistic regression, integrating alternative data sources to improve model precision and reduce default probability.
Clinical Data Science
Conducting statistical analyses in R for clinical trials and wound-care research, including experiment design, hypothesis testing, bias-detection, causal-inference studies, and integration of structured and unstructured EHR data.
Project history
Architected a production multi-agent system for commerce over the Model Context Protocol (MCP). Built citation-first RAG using cosine-similarity retrieval. Implemented responsible-AI guardrails with spaCy. Built two-stage demand forecasting using computer-vision car-park counts feeding XGBoost and Prophet. Developed sentiment analysis of discussion-platform comments using Naive Bayes, KNN, and GLMs.
Built predictive models forecasting steel demand using Python, SQL, R and Tableau. Engineered a custom Grid Search cross-validation approach for time-series data. Delivered Tableau dashboards of production data and KPI trends with documented model architectures and retraining protocols.
Led identification, measurement and control of risks from business activities. Applied advanced analytical techniques to medium- and large-scale business problems. Translated findings into communication materials and visualisations for varied management levels.