Data Scientist

<p></p> <p><strong>Data Scientist | Semiconductor Metrology</strong><br>Abingdon, UK</p> <p><strong>Reward and Benefits</strong></p> <ul> <li>£42,000 - £55,000 (depending on experience)</li> <li>Annual bonus, 3x salary death in service benefit and private health care BUPA, EMI Share scheme.</li> </ul> <p>If you are a Data Scientist who enjoys turning instrument data into proof of what is possible, why not join us in Abingdon, Oxfordshire, and help prove the analysis methods behind advanced semiconductor metrology systems.</p> <p>We are looking for an ambitious and adaptable Data Scientist to join our new Data Science team in the Technology department, reporting to the Data Science Lead and working closely with our Modelling Scientist. You will generate and curate data, develop and test new algorithms, and benchmark them against what the instrument can physically deliver. When a method proves itself, you will package it for the Data Analysis team in Engineering, who turn it into robust product software. You will work with real customer use cases and wafer data from Applications Development, and proof-of-concept data from R&amp;D.</p> <p>We are an AI-first team, so you will use AI tools every day, while checking carefully what they produce. If your passion is speed, evidence and finding out what the data can really tell you, we’d love to hear from you.</p> <p><strong>What you’ll be doing</strong></p> <ul> <li>Generate synthetic data, and build and maintain the demo and performance data libraries</li> <li>Analyse instrument data to quantify noise and limitations, and help establish the information limit, meaning what is physically extractable from the instrument</li> <li>Develop and test new algorithms and analysis methods (for example PCA, percentile methods and machine learning) on real and synthetic data</li> <li>Benchmark methods against the information limit: achievable performance, measurement uncertainty, gauge R&amp;R and drift contributors</li> <li>Write clean, reproducible prototype code with test data and expected performance, ready to hand over to Data Analysis, and build analysis tools used across the Technology department</li> <li>Use AI tools every day to code, explore, analyse and report faster, verify what they produce, and present your results to the team</li> </ul> <p><strong>Education and experience</strong></p> <ul> <li>Degree or above in Physics, Data Science, Applied Mathematics, Engineering or a similar subject, or [2] years’ relevant experience in data science or quantitative research</li> </ul> <p><strong>Skills and experience we’re looking for:</strong></p> <ul> <li>Data analysis in Python (