{"id":1282784,"url":"https://alion.io/job/permutable-graduate-quantitive-researcher","title":"Graduate Quantitive Researcher","company":{"id":2639686,"name":"Permutable","domain":"permutable.ai","url":"https://alion.io/company/permutable","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Git","optional":true},{"name":"LLM","optional":true},{"name":"Machine Learning","optional":true},{"name":"NLP","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-09-24T00:00:00Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-28T04:37:00Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About Permutable\nPermutable is a UK-based artificial intelligence and market intelligence company building data and quantitative products for global financial markets. We transform large volumes of multilingual news, economic, market and alternative data into structured signals that can be researched, tested and used by institutional investors, trading desks and other market participants.\nOur work sits at the intersection of quantitative finance, alternative data and AI. We develop proprietary datasets and systematic signals across areas including commodities and global macro, with the objective of turning complex real-world information into measurable and investable market intelligence.\nAbout the role\nPermutable is looking for a talented Graduate Quantitative Researcher to help us discover, develop and backtest new systematic trading strategies using our proprietary datasets.\nThis is a hands-on research role for someone who enjoys markets, statistics and programming. You will take ideas from an initial hypothesis, test whether our data contains genuine predictive information, and help turn successful research into robust quantitative strategies and products.\nWhat you'll do\nResearch new systematic trading strategies using Permutable's proprietary datasets.\nBacktest our existing and newly developed data to identify predictive signals and potential sources of alpha.\nAnalyse signals across different markets, assets, regimes and time horizons.\nBuild and improve robust Python research and backtesting tools.\nTest techniques including normalisation, ranking, Z-scores, signal smoothing, regime filters and portfolio construction.\nEvaluate strategies using returns, volatility, Sharpe ratio, drawdown, turnover, correlation, capacity and transaction costs.\nPerform out-of-sample testing, walk-forward analysis and robustness checks to reduce overfitting and false discoveries.\nInvestigate combinations of alternative data, market data, fundamental information and AI-derived signals.\nResearch position sizing, portfolio construction and risk-management approaches.\nClearly document what was tested, why a strategy appears to work, and where it fails.\nWork with engineering and product teams to move successful research towards production and client delivery.\nRequirements\nWhat we're looking for\nBachelor's or Master's degree in Mathematics, Statistics, Physics, Computer Science, Engineering, Economics, Finance or another highly quantitative subject.\nStrong Python skills, particularly pandas, NumPy and scientific/data-analysis libraries.\nGood understanding of statistics, probability and time-series analysis.\nAbility to work with large datasets and independently investigate patterns in data.\nA genuine interest in financial markets and systematic trading.\nUnderstanding of concepts such as returns, volatility, correlation, Sharpe ratio and drawdown.\nStrong analytical thinking and a willingness to challenge results rather than simply optimise a backtest.\nAbility to communicate quantitative research clearly to both technical and non-technical colleagues.\nNice to have\nExperience with any of the following would be useful, but isn't required:\nQuantitative finance, systematic trading or academic research projects.\nCommodities, futures, rates or FX.\nMachine learning applied to financial time series.\nAlternative data, NLP or LLM-derived signals.\nPortfolio optimisation and risk models.\nGit, SQL and cloud-based data environments.\nPersonal quantitative research, trading competitions or other evidence of independently testing ideas with data.\nWhat makes the role interesting\nYou won't simply maintain existing models. You'll be given access to proprietary datasets and asked questions such as:\nDoes this dataset contain tradable information?\nWhich markets does it predict?\nAt what horizon does the signal work?\nIs the result robust, or are we overfitting? Can we turn it into a strategy that survives transaction costs and out-of-sample testing?\nSuccessful research can ultimately contribute to quantitative research and data products used by institutional clients.\nBenefits\nHands-On Research: Work directly with proprietary datasets and test whether they contain genuine predictive information.\nDevelop Your Quant Skills: Build practical experience in systematic trading, backtesting, statistics, portfolio construction and financial markets.\nAI & Alternative Data: Work with innovative datasets, AI-derived signals and large volumes of financial and alternative data.\nReal Impact: Successful research can contribute to quantitative products used by institutional financial clients.\nLearn Across Teams: Work closely with experienced colleagues across quantitative research, engineering and product.\nAn Ambitious, Collaborative Culture: Join a close-knit team with the pace, openness and shared sense of purpose of a high-growth start-up. We work together from our Vauxhall hub and make time for regular team socials and company offsites.","description_format":"text","description_chars":4964,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Natural Language Processing","Financial Data & Market Intelligence"],"lifecycle":[{"event":"open","at":"2026-09-26T03:38:03Z"}],"liveness":{"score":84,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.838,"p_room":1,"age_days":4,"expected_fill_days":15,"reasons":["conf:1","velocity","win:early","comp:junior"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/permutable-graduate-quantitive-researcher","json_url":"https://alion.io/job/permutable-graduate-quantitive-researcher.json","meta":{"generated_at":"2026-09-28T06:35:11Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4655,"day_limit":5000,"remaining_today":345,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}