101 to 125 of 326 Remote Algorithms Jobs

market connectivity and trading systems in a fast-paced Front Office environment. Responsibilities include: - Develop high-performance eFX pricing and connectivity services - Support trading algorithms and real-time analytics - Prototype and deliver solutions quickly for Front Office - Work across design, development, testing and release - Provide 3rd-line support and ensure ...

project for a fully operational capability. Responsibilities: Developing and testing complex C++ business logic. Collaboration with internal algorithm teams to create code to execute algorithms, implement complex transformation logic and verification implementation. We expect several iterations using a CI/CD approach. Implementation of interfaces to internal and external systems. ...

data to make data-driven decisions Stay up-to-date with the latest trends and best practices in technical SEO and search engine algorithms Collaborate, mentor and support other members of the marketing team to integrate multi-disciplinary initiatives with other marketing channels (e.g. social media, PR & content marketing, etc. ...

Software Engineers , depending on depth of experience and appetite for technical leadership. What youll be working on Youll be turning clever DSP and comms algorithms into real-time production software running on x86 or ARM , and building high-performance APIs that interface with hardware acceleration. Expect a mix of: Real ...

WhiteSpace Solutions, we bring care back to critical decisions. Our AI-powered solutions don't replace human judgment - they elevate it. By combining advanced algorithms with deeply human interfaces, we turn complexity into clarity and confident action. Always with fast time to value. Our proprietary platform underpins high-impact optimisation ...

Hopper's mobile app, website and our B2B business, HTS (Hopper Technology Solutions). By leveraging massive amounts of data and advanced machine learning algorithms, Hopper combines its world-class travel agency offering with proprietary fintech products to bring transparency, flexibility and savings to travelers globally. We have developed several ...

dynamic, interconnected ecosystem spanning multiple locations and entities, where complex constraints and resource interdependencies - among people, machines, and robots - demand the deployment of intelligent algorithms for orchestration, informed decision-making, and planning. Our research pioneers such algorithms grounded in cutting-edge Data Science techniques, with a focus on intelligent exploitation … solution approaches) Integrated supply chain planning (topical side: e.g., variants of production routing problem, flexible job shop problem; methodological side: e.g., advanced decomposition algorithms, customized constraint propagation techniques, hybrid combinatorial and AI solution approaches). Additionally, you will be involved and collect experience in supervision of PhD students, teaching ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...

clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations and experimental design Cohort analysis and retention rate computations Model evaluation metrics … corrections Causal inference: propensity score matching, difference-in-differences Complex ETL pipeline logic and multi-source data integration Missing data imputation and outlier detection algorithms Feature engineering: encoding, interactions, dimensionality reduction Time Series & Forecasting Trend decomposition and seasonality detection Stationarity testing and autocorrelation calculations Forecast accuracy metrics and moving average ...