existing systems, enabling customers to see what's important and change outcomes. Reporting to: Head of Global Business Delivery Key Responsibilities: Work with Commercial Delivery team to: Conduct data analysis based on current deployments and communicate key insights through reports, presentations and visualisations to stakeholders. Manage external and internal video analysis teams, perform moderation of results to ensure … consistency of outputs in order to deliver reporting in accordance with client reporting schedule. Use video analysis outputs to generate regular internal assessments of the solution performance, identify areas of improvement and guide product requirements to achieve a solution performance level which meets customer expectations. Support business scaling as needed: e.g. build internal and external reporting required for tracking … complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), PrincipalComponentAnalysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and build convincing stories. Good communication and problem-solving skills. Good organisational skills. Excellent time management. More ❯
existing systems, enabling customers to see what's important and change outcomes. Reporting to: Head of Global Business Delivery Key Responsibilities: Work with Commercial Delivery team to: Conduct data analysis based on current deployments and communicate key insights through reports, presentations and visualisations to stakeholders. Manage external and internal video analysis teams, perform moderation of results to ensure … consistency of outputs in order to deliver reporting in accordance with client reporting schedule. Use video analysis outputs to generate regular internal assessments of the solution performance, identify areas of improvement and guide product requirements to achieve a solution performance level which meets customer expectations. Support business scaling as needed: e.g. build internal and external reporting required for tracking … complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), PrincipalComponentAnalysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and build convincing stories. Good communication and problem-solving skills. Good organisational skills. Excellent time management. More ❯
detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised … algorithms (k means clustering, PrincipalComponentAnalysis, Market Basket analysis). Experience in solving optimization problems like inventory and network optimization. Should have hands on experience in Linear Programming. Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area. Detail-oriented and must … data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience - Experience applying theoretical models in an applied environment PREFERRED QUALIFICATIONS - Experience in Python, Perl, or another scripting language - Experience More ❯
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 ❯
products Support the development of a MySQL-based engineering database, integrating real-time sensor and assay performance data Implement multivariate computational models (e.g., PrincipalComponentAnalysis (PCA), Partial Least Squares (PLS)) to identify key measurement variables within complex electrochemical datasets. Develop non-linear regression models to improve the accuracy of immunoassay data analysis. Apply machine learning techniques … Strong experience in computational modelling, data analysis, and machine learning techniques. Proficiency in Python, R, MATLAB, or other statistical programming languages. Knowledge of multivariate analysis techniques (e.g., PCA, PLS) and non-linear regression models. Experience developing predictive machine learning algorithms (e.g., Random Forest, Neural Networks). Proficiency in SQL (preferably MySQL) and database management for engineering data storage 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 ❯
around model monitoring, performance tracking, and data drift. Strong SQL skills for data extraction, joining, and transformation. Preferred Skills : Familiarity with unsupervised learning methods such as K-means, DBSCAN, PCA, or autoencoders, and their application in credit use cases like behavioral segmentation, fraud detection, or exploratory analysis Experience working in a start-up or scale-up environment with fast More ❯
methodsExperience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etcExperience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomesAdvanced understanding of Python and More ❯
Technology, or Engineering. Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods. Experience with models like regression, tree-based models, support vector machines, PCA, clustering, matrix factorization, deep learning, etc. Proficiency in Python and its machine learning ecosystem (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch). Knowledge of SQL and experience with relational databases. Agile More ❯
Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc Experience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomes Advanced understanding of More ❯
Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc Experience using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomes Advanced understanding of 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 ❯
Luton, Bedfordshire, United Kingdom Hybrid / WFH Options
Leonardo UK Ltd
Job Description: Title: Principal Configuration Engineer - Luton Site Company Overview: Leonardo is a global high-tech company and a key player in Aerospace, Defence, and Security. Headquartered in Italy, Leonardo has over 45,000 employees and a significant industrial presence in Italy, the United Kingdom, the United States, and Poland, along with a network of strategic partnerships worldwide. Role … Leonardo UK is advancing in areas such as tactical sensing, data fusion, communications, machine learning, and defensive systems. This role offers a unique opportunity to contribute significantly as a Principal Configuration Engineer based at our Luton Site with hybrid working arrangements. Responsibilities: Lead the five key Configuration activities across all lifecycle phases of a Programme within IPTs. Provide clear More ❯
Snr. ProServe Cloud Architect, Professional Services The Amazon Web Services Professional Services (ProServe) team is seeking an experienced ProServe Cloud Architect (PCA) to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to understand their technical requirements and business objectives, designing and implementing tailored cloud solutions. You'll be a key … Account Executives and our Shared Delivery Teams (SDT), you'll ensure proposed solutions are realistic, achievable, and optimize ProServe and/or our partners to maximize CBOs. As a PCA you are a trusted advisor to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions to address customer challenges. As a technical SME, you will share knowledge … with the ability to architect complex, scalable, and secure solutions tailored to meet the specific needs of each customer, translating technical concepts into business value. Your success as a PCA will be linked to impacting the signing of SOWs, and the successful implementation of solutions which achieve CBOs while exceeding customer satisfaction (CSAT) expectations. The AWS Professional Services organization is More ❯
