3 of 3 Principal Component Analysis Jobs in London

translate data insights into actionable recommendations. You should be comfortable working independently in a fast-paced, ambiguous environment. Key Responsibilities Perform feature engineering on large datasets, conduct exploratory data analysis, and … build models using time series forecasting techniques such as ARIMA, ARIMAX, Holt Winter, and ensemble methods. Apply supervised learning algorithms (linear/logistic regression) and unsupervised algorithms (k-means, PCA, market basket analysis). Solve optimization problems related to inventory and network optimization, with hands-on experience in linear programming. Collaborate with business, engineering, and partner teams to align More ❯

clients and internal stakeholders. An eagerness to learn on the job is also required, with the company increasingly offering advanced analytical approaches to clients such as driver and factor (PCA) analysis, customer segmentation, maxdiff, conjoint etc... Prospective candidates need to be well-rounded individuals that work well within a friendly team culture and have strong analytical and communications skills. More ❯

science, math, finance or engineering). 9 years of experience in fixed income quantitative research (buy-side preferred) Deep knowledge and understanding of statistical theory and methods, for example, PCA, linear/quadratic/mixed integer optimization, classification, feature identification and selection, multi-variable regressions, and their practical applications, tricks and best practices. Experience and understanding of factor risk and More ❯