Prediction Markets Quantitative Engineer

**About G20 Group** G-20 Group is a leading cross-asset trading firm active in delta-one and derivatives markets. Established in 2010, G-20 offers liquidity solutions, treasury management, and institutional advisory services. We are supported by an outstanding team of professionals, with a robust global presence in EMEA, Americas, and APAC. **Role Overview** We are hiring a **Prediction Markets Quant Engineer** to build research and trading infrastructure for operating in prediction markets (event contracts) across multiple venues. You will design models that estimate event probabilities, detect mispricing, size positions, and manage risk – then translate them into reliable systems that run end-to-end (data → forecasting → execution → monitoring). This role sits at the intersection of quant research, engineering, and market microstructure, and is ideal for someone who enjoys shipping robust systems as much as developing models. **Responsibilities** ***Modeling & Research*** - Develop probabilistic models to forecast outcomes of real-world events (e.g., elections, macro releases, sports, policy decisions, industry milestones). - Combine heterogeneous signals (time series, text/news, market data, polling/alternative data, fundamentals, expert priors) into calibrated probability estimates. - Build pricing and edge frameworks: fair value, uncertainty bands, expected value, and model drift/regime diagnostics. - Design evaluation methods (proper scoring rules like log loss/Brier score, calibration curves, back-tests with realistic costs and constraints). ***Trading & Market Design (Applied)*** - Identify and exploit mis-pricings across contracts/venues; design cross-market arbitrage and relative-value strategies where feasible. - Build position sizing and risk frameworks (Kelly variants, drawdown/risk budgets, scenario stress tests, liquidity/impact-aware sizing). - For multi-outcome markets: enforce probability coherence (no-arb constraints, normalization) and portfolio optimization across correlated contracts. ***Engineering & Production*** - Build data pipelines and real-time services for ingesting, cleaning, and versioning market + external data. - Implement execution tooling: order management, smart routing (where applicable), monitoring, and automated safeguards. - Create dashboards/alerts for performance, exposure, model health (calibration, drift), and operational integrity. - Ensure reproducibility: experiment tracking, model registry, CI/CD, and robust testing. ***Collaboration & Governance*** - Work closely with trading/risk/compliance stakeholders to translate research into controlled deployment. - Document models, assumptions, failure modes, and operating procedures; participate in incident reviews and continuous improvement. - Degree in Quantitative Finance, Mathematics, Computer Science, Statistics, or a related quantitative field. - Strong engineering skills with Python (required); experience with production systems and data engineering. - Solid foundation in statistics, probability, and machine learning (calibration, uncertainty, causal pitfalls, time-series). - Experience building backtests and evaluating predictive models with appropriate metrics (e.g., log loss/Brier, calibration). - Familiarity with trading concepts: expected value, position sizing, risk budgeting, correlation, liquidity constraints. - Ability to communicate clearly about model assumptions, limitations, and risk. - Some schedule flexibility may be required around major event windows - Self-motivated, detail-oriented, and comfortable working in a dynamic, startup-like environment. **Preferred / Desirable Experience** - Prior work in forecasting, sports analytics, political modeling, event-driven trading, or market-making/liquidity modeling. - Experience with NLP for news/social/media signals; knowledge graphs or information retrieval for event resolution. - Knowledge of prediction market mechanics (order books vs AMMs, fee structures, market man…