Assistant Vice President

Job Summary: We are seeking a Senior Project Manager (Analytics & Data Projects) with a strong background in data analytics and technical project delivery. The ideal candidate has hands-on knowledge of SQL and Python , with exposure to Data Science and Data Engineering workflows , and proven experience in leading cross-functional teams. This role requires a strategic mindset, technical acumen, and excellent leadership to manage complex analytics initiatives from planning through execution. Key Responsibilities: Project & Delivery Management: Lead end-to-end delivery of data and analytics projects, including scoping, planning, execution, risk management, and stakeholder communication. Define project objectives, scope, timelines, and resource needs in collaboration with business and technical teams. Drive Agile/Scrum or hybrid project methodologies, ensuring deliverables are on time and within scope. Manage cross-functional teams including Data Engineers, Data Analysts, and Data Scientists. Technical Understanding & Oversight: Guide the development of data pipelines, analytics dashboards, and machine learning solutions. Understand and oversee usage of SQL and Python in analytics workflows (e.g., data wrangling, automation, modeling). Liaise with technical leads to ensure data quality, security, and performance standards are met. Translate complex technical requirements into clear, actionable tasks for team members. Team & Stakeholder Management: Lead and mentor a team of analysts and engineers; perform capacity planning and performance reviews. Serve as the primary liaison between business stakeholders and technical teams. Drive alignment between analytics initiatives and business goals. Prepare and deliver executive-level reporting on project status, risks, and milestones. Required Skills and Experience: 8+ years of overall experience with at least 35 years in project/program management , especially in data analytics or technology projects

• Proven expertise in managing technical teams and large-scale data projects. Solid hands-on understanding of SQL and Python in the context of data analysis and ETL workflows. Exposure to Data Science tools and frameworks (e.g., scikit-learn, pandas, Jupyter) and Data Engineering concepts (e.g., data lakes, ETL, pipelines)
• Experience with tools such as JIRA, Azure DevOps, Trello, Confluence , or similar for project tracking. Strong knowledge of Agile, Scrum, and/or traditional project management methodologies
• Excellent communication, leadership, and stakeholder management skills. Preferred Qualifications: PMP, Prince2, or Agile/Scrum certification. Familiarity with cloud platforms like AWS, Azure, or GCP. Experience with BI tools (Power BI, Tableau) and version control (Git). Background in computer science, data analytics, or related technical discipline.