Data Science AI Engineer

About the role

Analyze historical data to identify predictive features and business-relevant patterns. Develop time-series forecasting models (Prophet, ARIMA, LSTM, XGBoost) tailored to project and quantify forecast accuracy against agreed thresholds. Build a Conversational AI layer using Azure OpenAI + RAG patterns to enable naturallanguage queries over financial and workforce data.

What you'll do

• Own the design, development, validation, and productionization of AI/ML models for financial forecasting
• Analyze historical data to identify predictive features and business-relevant patterns
• Develop time-series forecasting models (Prophet, ARIMA, LSTM, XGBoost) tailored to project and quantify forecast accuracy against agreed thresholds
• Build a Conversational AI layer using Azure OpenAI + RAG patterns to enable naturallanguage queries over financial and workforce data
• Partner with FP&A SMEs to translate business drivers into model features and interpretable outputs

What you need

• 6–8 yrs of experience
• Machine learning
• Python
• Pandas
• Scikit-learn
• MLOps
• LLMs
• Any graduate

Good to have

• Deep learning
• Prompt engineering
• NumPy
• Azure
• FP&A
• AML