Machine Learning and Quant Engineer - London

<p data-start="450" data-end="809">You think in time series, signals, and regimes.<br>You care about insight quality, not academic purity.<br>You want your models tested by markets, not papers.<br>If you dislike messy data and real-world constraints, this is not your role.</p> <h2 data-start="811" data-end="840">The Role, In Plain English</h2> <p data-start="841" data-end="1205">You will build quantitative and ML-driven insight systems using structured time series data.<br>This role exists to turn raw financial data into actionable investor signals.<br>You will work closely with engineers to productionize quant logic.</p> <h2 data-start="1207" data-end="1240">What You’ll Be Responsible For</h2> <ul> <li>Develop models using structured financial time series</li> <li>Build insight generation and scenario analysis pipelines</li> <li>Collaborate with backend engineers to deploy models in production</li> <li>Evaluate signals based on real investor outcomes</li> <li>Improve attribution and explainability</li> </ul> <h2 data-start="1730" data-end="1768">What “Good” Looks Like in This Role</h2> <p data-start="1769" data-end="1895"><strong data-start="1769" data-end="1788">After 3 months:</strong><br data-start="1788" data-end="1791">Shipping signals used internally.</p> <p data-start="1897" data-end="2014"><strong data-start="1897" data-end="1916">After 6 months:</strong><br data-start="1916" data-end="1919">Signals used by customers.</p> <p data-start="2016" data-end="2146"><strong data-start="2016" data-end="2036">After 12 months:</strong><br data-start="2036" data-end="2039">You shape how quant insights are built at Reflexivity.</p> <h2 data-start="2148" data-end="2175">Who You Are (Must-Haves)</h2> <ul> <li>5 plus years experience in quant, ML, or financial modeling</li> <li>Strong Python skills</li> <li>Startup experience on core systems</li> <li>Investment domain knowledge</li> <li>AI-assisted coding experience</li> </ul> <h2 data-start="2575" data-end="2611">Nice-to-Haves (Not Deal Breakers)</h2> <ul> <li>Prior buy-side or sell-side experience</li> <li>Experience with alternative data</li> </ul> <h2 data-start="2775" data-end="2789">How We Work</h2> <ul> <li data-start="2792" data-end="2843">In-office team with high trust and high ownership</li> <li data-start="2846" data-end="2917">Direct communication, minimal process, strong opinions backed by data</li> <li data-start="2920" data-end="2989">Engineers are expected to think about product impact, not just code</li> <li data-start="2992" data-end="3064">We move fast when it matters and slow down when correctness matters more</li> </ul> <h2 data-start="3066" data-end="3101">Why This Role Is Worth Your Time</h2> <ul> <li data-start="3104" data-end="3167">Direct influence on how professional investors make decisions</li> <li data-start="3170" data-end="3222">Hard problems at the edge of AI, data, and finance</li> <li data-start="3225" data-end="3264">Real ownership and technical autonomy</li> <li data-start="3267" data-end="3315">Senior peers who care about quality and outcomes</li> </ul> <h2 data-start="3317" data-end="3349">Compensation &amp; Practicalities</h2> <ul> <li data-start="3352" data-end="3411">Base salary: £110,000 to £200,000 depending on experience</li> <li data-start="3414" data-end="3431">Equity included</li> <li data-start="3434" data-end="3468">In-office role based in London</li> <li data-start="3471" data-end="3491">No agency candidates</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="title">Salary Range</div><div class="pay-range"><span>£110,000</span><span class="divider">&mdash;</span><span>£200,000 GBP</span></div></div></div>