Stellenbeschreibungph3About G20 Group /h3 pG-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. /p h3Role Overview /h3 pWe 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). /p pThis 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. /p h3Responsibilities /h3 h3Modeling Research /h3 ul liDevelop probabilistic models to forecast outcomes of real-world events (e.g., elections, macro releases, sports, policy decisions, industry milestones). /li liCombine heterogeneous signals (time series, text/news, market data, polling/alternative data, fundamentals, expert priors) into calibrated probability estimates. /li liBuild pricing and edge frameworks: fair value, uncertainty bands, expected value, and model drift/regime diagnostics. /li liDesign evaluation methods (proper scoring rules like log loss/Brier score, calibration curves, back-tests with realistic costs and constraints). /li /ul h3Trading Market Design (Applied) /h3 ul liIdentify and exploit mis-pricings across contracts/venues; design cross-market arbitrage and relative-value strategies where feasible. /li liBuild position sizing and risk frameworks (Kelly variants, drawdown/risk budgets, scenario stress tests, liquidity/impact-aware sizing). /li liFor multi-outcome markets: enforce probability coherence (no-arb constraints, normalization) and portfolio optimization across correlated contracts. /li /ul h3Engineering Production /h3 ul liBuild data pipelines and real-time services for ingesting, cleaning, and versioning market + external data. /li liImplement execution tooling: order management, smart routing (where applicable), monitoring, and automated safeguards. /li liCreate dashboards/alerts for performance, exposure, model health (calibration, drift), and operational integrity. /li liEnsure reproducibility: experiment tracking, model registry, CI/CD, and robust testing. /li /ul h3Collaboration Governance /h3 ul liWork closely with trading/risk/compliance stakeholders to translate research into controlled deployment. /li liDocument models, assumptions, failure modes, and operating procedures; participate in incident reviews and continuous improvement. /li liDegree in Quantitative Finance, Mathematics, Computer Science, Statistics, or a related quantitative field. /li liStrong engineering skills with Python (required); experience with production systems and data engineering. /li liSolid foundation in statistics, probability, and machine learning (calibration, uncertainty, causal pitfalls, time-series). /li liExperience building backtests and evaluating predictive models with appropriate metrics (e.g., log loss/Brier, calibration). /li liFamiliarity with trading concepts: expected value, position sizing, risk budgeting, correlation, liquidity constraints. /li liAbility to communicate clearly about model assumptions, limitations, and risk. /li liSome schedule flexibility may be required around major event windows. /li liSelf-motivated, detail-oriented, and comfortable working in a dynamic, startup-like environment. /li /ul h3Preferred / Desirable Experience /h3 ul liPrior work in forecasting, sports analytics, political modeling, event-driven trading, or market-making/liquidity modeling. /li liExperience with NLP for news/social/media signals; knowledge graphs or information retrieval for event resolution. /li liKnowledge of prediction market mechanics (order books vs AMMs, fee structures, market manipulation/anti-manipulation signals). /li liProficiency with SQL; experience with streaming systems (Kafka), workflow orchestration (Airflow), and cloud (AWS/GCP/Azure). /li liExperience with Bayesian methods, probabilistic programming (Stan/PyMC), or ensemble methods. /li liFamiliarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. /li /ul h3Tech Stack /h3 ul liPython, SQL, pandas/numpy/scipy, PyTorch/sklearn /li liAirflow/dbt, Kafka (or equivalents), Postgres/BigQuery /li liDocker, Kubernetes (optional), CI/CD (GitHub Actions) /li liObservability: Prometheus/Grafana, OpenTelemetry (or equivalents) /li /ul h3Locations and Right to work /h3 pThis role can be based out of our Zurich, London, New York or Hong Kong office. Only candidates who possess the pre-existing right to work in one of the locations above without company sponsorship need apply. /p pJoin G-20 and be a part of a team that is at the forefront of financial markets, driving innovation and excellence in the sector. /p /p #J-18808-Ljbffr
