learn more about LexisNexis Risk at the link below, risk.lexisnexis.com About our Team: You will part of a small team assisting the business with statisticalanalysis and building predictive models for credit, fraud, and risk. About the Role: We are looking for a Data Scientist to conduct statisticalanalysis and build predictive models for credit, fraud, and risk. The ideal candidate will have experience in data mining, statistical methods, and modelling/scoring techniques. They will balance day-to-day analytics assignments, research experiments and will contribute to the advancement of the global data science … group. Responsibilities Building and testing credit and fraud risk statistical models, consulting in support of existing and new customer sales Providing complex analytical results in clear, simple messaging to evidence the value provided by our products Following modelling best practices and provide feedback on ways to enhance current processes more »
support third party and customer audits on site. Regular communication with customers for New Product development, product approval and complaints Establish and define competent statisticalanalysis, monitoring quality control data to identify trends, deviations, and potential issues, and implement corrective actions as needed. Collaborate with laboratory staff to … to enhance laboratory efficiency and effectiveness. Provide guidance and support to laboratory staff on quality-related matters, including the interpretation of regulations and standards. Analysis of laboratory performance data to provide feedback regarding manufacturing processes to improve product performance. Requirements: Performance Expectations Measurement System Analysis methodologies, particularly using … statisticalanalysis techniques are important for this role. A good understanding of UKAS accreditations would be beneficial. Monitor product and laboratory performance to ensure methods are followed accurately, tests meet acceptance criteria and proficiency work is satisfactory. Required Qualifications Bachelor's degree in a relevant field (e.g., quality more »
models.Key Tasks: Fraud Detection: Access existing systems, evaluate vendor models, and create a roadmap for system improvements aimed at fraud prevention. Pattern and Irregularity Analysis: Use statistical tools to uncover patterns and irregularities in data that could indicate fraudulent activities. Predictive Modelling: Employ predictive modelling techniques to identify … Cross-Department Collaboration: Work closely with other departments to enhance overall security and fraud detection.Requirements: Programming Proficiency: Fluency in Python with deep knowledge of statistical packages and ML/DL libraries/frameworks (e.g., Scikit-learn, NumPy, Keras/TensorFlow/PyTorch) and visualization libraries (e.g., Matplotlib, Plotly, Seaborn … . Database Skills: Fluency in SQL and familiarity with data visualization tools (e.g., DataStudio, Tableau). StatisticalAnalysis: Basic understanding of statistical analysis. Growth Mindset: Proactive and enthusiastic about keeping up-to-date with the latest technologies and researching new ideas. Commercial Experience: Experience in implementing production more »
e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statisticalanalysis knowledge. - Experience in deploying production ML systems. - Familiarity with DevOps in a data science context (e.g., MLOps) is a plus. Tools currently more »
e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statisticalanalysis knowledge. - Experience in deploying production ML systems. - Familiarity with DevOps in a data science context (e.g., MLOps) is a plus. Tools currently more »
post; English and/or Welsh speakers are equally welcome to apply. Person Specification Qualifications Essential Educated to Masters level in human resources or statisticalanalysis, or demonstrated equivalent level of experience Professional qualification in Human Resources: Chartered Member - MCIPD Extensive specialist knowledge required over a range of more »
test and characterization methodologies for silicon carbide power semiconductor devices to understand their reliability and failure mechanisms in operation. Design experiments and co-ordinate statistical studies to determine device reliability, for example gate oxide lifetime marathon test, time-dependent dielectric breakdown. Develop screening and burn-in procedures for SiC … the field of semiconductor technology; Experience in reliability testing of SiC MOSFETs and diodes, both at wafer- and package-level; A good understanding of statisticalanalysis and design of experiments; Knowledge of semiconductor TCAD tools for device simulation, i.e. Synopsys Sentaurus, Silvaco Victory; Background in electronics engineering for more »