Danius Jean Backis

Data Scientist @ING

London, GB

At ING I worked on the electronic fixed income desk, developing pricing and trading algorithms for corporate bonds. Key contributions- Designed and implemented ING’s trading algorithm, which dynamically adjusts client prices depending on our position, risk contribution, and balance sheet impact. Enhanced it further by integrating portfolio theory concepts (efficient frontier, Sharpe ratio) and repo costs- Built logistic regression–based RFQ win-probability models incorporating price, tier, trade size, number of dealers, and interaction terms, to inform pricing and client strategy- Developed frameworks to quantify how each trade moved our portfolio towards or away from optimal weights. Incorporated repo, liquidity forecasts, and client quality into the pricing logic- Maintained the desk’s data pipelines in kdb+/q and Python, including real-time RFQ filtering, CBBT/CP+ benchmark spread analysis, and liquidity prediction models.