7 77664 Jobs

Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.