Padmi

Title Lead Analyst Machine Learning Forecasting (Noida)

Delhi NCRPosted 1 month ago
Data Science And StatisticsSeniorFull Time; Regular
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Job Title: Lead Analyst Machine Learning Forecasting Location: Noida Job Type: Full-Time Role Overview Seeking an experienced Assistant Manager Machine Learning Forecasting to lead advanced predictive modeling initiatives and drive strategic insights for business planning. This role requires solid expertise in statistical modeling, machine learning algorithms, and data engineering, combined with leadership skills to manage projects and mentor team members. Key Responsibilities - Lead end-to-end forecasting strategy using advanced statistical and machine learning models (ARIMA, SARIMA, ETS, Holt-Winters, etc.) for complex business scenarios. - Own forecasting lifecycle from data acquisition, preprocessing, and model development to deployment and performance optimization. - Design scalable data pipelines and ETL processes leveraging Azure Data Factory (ADF) and other cloud-based tools. - Implement automation and optimization for forecasting workflows to improve efficiency and accuracy. - Develop advanced data collection techniques , including Python-based web scraping and API integrations for real-time data ingestion. - Perform deep-dive analytics and visualization using MS Excel, Power BI, or similar tools to support decision-making. - Collaborate with cross-functional teams (Operations, Marketing, Finance) to incorporate qualitative insights and align forecasts with business objectives. - Ensure data security and compliance , including MFA implementation and governance standards. - Mentor junior analysts and contribute to building forecasting best practices across the organization. - Present strategic insights and recommendations to senior leadership through impactful reports and presentations. Requirements - 5+ years of experience in forecasting, machine learning, and statistical modeling. - Proven expertise in Python , Azure Data Factory , and ETL design. - Strong knowledge of time-series forecasting techniques and accurately testing methodologies. - Excelle .

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