Lead Analyst - Machine Learning Forecasting

As a Lead Analyst specializing in Machine Learning Forecasting, your role involves spearheading advanced predictive modeling projects and providing strategic insights for business planning. Your responsibilities will include: - Leading end-to-end forecasting strategies utilizing advanced statistical and machine learning models such as ARIMA, SARIMA, ETS, and Holt-Winters for complex business scenarios. - Taking charge of the forecasting lifecycle from data acquisition, preprocessing, model development to deployment, and performance optimization. - Designing scalable data pipelines and ETL processes by leveraging tools like Azure Data Factory (ADF) and other cloud-based solutions. - Implementing automation and optimization techniques to enhance the efficiency and accuracy of forecasting workflows. - Developing advanced data collection techniques, involving Python-based web scraping and API integrations for real-time data ingestion. - Conducting in-depth analytics and visualization using tools like MS Excel, Power BI, or similar platforms to facilitate decision-making. - Collaborating with cross-functional teams to integrate qualitative insights and align forecasts with business objectives. - Ensuring data security and compliance by implementing Multi-Factor Authentication (MFA) and adhering to governance standards. - Mentoring junior analysts and contributing to the establishment of forecasting best practices within the organization. - Presenting strategic insights and recommendations to senior leadership through impactful reports and presentations. To qualify for this role, you should possess: - 5+ years of experience in forecasting, machine learning, and statistical modeling. - Proficiency in Python, Azure Data Factory, and ETL design. - Sound knowledge of time-series forecasting techniques and validation methodologies. - Strong analytical, problem-solving, and stakeholder management skills. - The ability to independently lead projects and manage multiple priorities. - Excellent communication and presentation skills suitable for executive-level reporting. Preferred qualifications include experience in Contact Center or Service Operations forecasting, familiarity with AI/ML frameworks and cloud-based data solutions, and an advanced degree in Data Science, Statistics, Computer Science, or a related field. If you are interested in this opportunity and meet the requirements, please share your updated CV on the provided email address for further consideration. As a Lead Analyst specializing in Machine Learning Forecasting, your role involves spearheading advanced predictive modeling projects and providing strategic insights for business planning. Your responsibilities will include: - Leading end-to-end forecasting strategies utilizing advanced statistical and machine learning models such as ARIMA, SARIMA, ETS, and Holt-Winters for complex business scenarios. - Taking charge of the forecasting lifecycle from data acquisition, preprocessing, model development to deployment, and performance optimization. - Designing scalable data pipelines and ETL processes by leveraging tools like Azure Data Factory (ADF) and other cloud-based solutions. - Implementing automation and optimization techniques to enhance the efficiency and accuracy of forecasting workflows. - Developing advanced data collection techniques, involving Python-based web scraping and API integrations for real-time data ingestion. - Conducting in-depth analytics and visualization using tools like MS Excel, Power BI, or similar platforms to facilitate decision-making. - Collaborating with cross-functional teams to integrate qualitative insights and align forecasts with business objectives. - Ensuring data security and compliance by implementing Multi-Factor Authentication (MFA) and adhering to governance standards. - Mentoring junior analysts and contributing to the establishment of forecasting best practices within the organization. - Presenting strategic insights and recommendations to senior leadership through impactful reports and presentations. To qualify for this role, you should possess: - 5+ years of experience in forecasting, machine learning, and statistical modeling. - Proficiency in Python, Azure Data Factory, and ETL design. - Sound knowledge of time-series forecasting techniques and validation methodologies. - Strong analytical, problem-solving, and stakeholder management skills. - The ability to independently lead projects and manage multiple priorities. - Excellent communication and presentation skills suitable for executive-level reporting. Preferred qualifications include experience in Contact Center or Service Operations forecasting, familiarity with AI/ML frameworks and cloud-based data solutions, and an advanced degree in Data Science, Statistics, Computer Science, or a related field. If you are interested in this opportunity and meet the requirements, please share your updated CV on the provided email address for further con