ITPM Budgeting in Analytics Space

Accountabilities •

Lead and manage end-to-end IT projects across data management, analytics, data science, visualization, big data, and AI/ML initiatives, from ideation through deployment and ongoing support.

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Oversee project planning, budgeting, resource allocation, timelines, deliverables, and execution to ensure successful and timely project completion.

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Drive the complete data science project lifecycle, including use case definition, data collection, data exploration, model development, deployment, and operational support.

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Manage projects across multiple geographical regions and business units, ensuring consistency, alignment, and effective collaboration between teams.

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Lead business and technical requirements gathering, combining business understanding with technical expertise to define appropriate solutions.

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Translate business requirements into technical solutions, estimate project effort, and coordinate with architects and technical stakeholders.

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Participate in solutioning, architecture design, technical reviews, and the preparation of project documentation and delivery artifacts.

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Review proposed solution designs, project estimates, and implementation plans to ensure alignment with client expectations and business objectives.

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Monitor project progress, identify critical tasks, anticipate risks and delays, and implement corrective actions to maintain delivery commitments.

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Manage internal and external stakeholder communications, providing regular updates on project status, budgets, funding, risks, and milestones.

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Define clear project plans, responsibilities, and expectations for team members while ensuring effective coordination across multidisciplinary teams.

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Measure and communicate the business value of delivered solutions to encourage adoption and maximize the impact of analytics initiatives.

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Resolve project challenges, remove organizational silos, facilitate problem-solving, and promote efficient collaboration between technical and business teams.

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Lead and motivate geographically distributed teams, ensuring accountability, performance, and alignment with project objectives.

Requirements:

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At least 12 years of overall professional experience in IT, data management, analytics, data science, or AI/ML, including a minimum of 4 years in project management.

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Strong technical background or solid understanding of data science, artificial intelligence, machine learning, and analytics-related technologies.

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Good knowledge of data warehousing, statistics, machine learning algorithms, cloud technologies, and their practical applications.

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Demonstrated experience managing end-to-end data science projects, covering use case framing, data collection, data exploration, model development, and deployment.

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Proven track record of successfully delivering and deploying projects in data science, data visualization, or big data environments, across on-premises and/or cloud infrastructure.

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Experience managing the complete product lifecycle, including ideation, development, deployment, AI/ML operations, and ongoing support.

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Strong project management capabilities, including planning, budgeting, effort estimation, resource management, risk mitigation, and delivery monitoring.

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Ability to lead requirements gathering, translate business needs into technical solutions, and collaborate effectively with architects on solution design.

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Experience reviewing technical architectures, project estimates, implementation approaches, and delivery documentation.

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Excellent stakeholder management and communication skills, with the ability to engage business leaders, technical teams, architects, and clients.

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Strong leadership and people management capabilities, particularly in coordinating and managing geographically distributed teams.

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Excellent problem-solving and decision-making skills, with the ability to overcome challenges, resolve conflicts, and improve collaboration across departments.

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Ability to manage multiple projects simultaneously while maintaining visibility over budgets, deliverables, deadlines, and dependencies.

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A graduate degree in any discipline is acceptable.

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Previous experience working with cloud platforms is an additional advantage.

Benefits:

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Competitive compensation: Annual salary ranging from INR 500,000 to INR 2,000,000, depending on experience and qualifications.

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Employment type: Full-time, permanent opportunity.

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Work flexibility: Remote working opportunity, with a hybrid working arrangement indicated for the role.

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Professional development: Opportunity to work on large-scale data science, analytics, and AI/ML projects.

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Technical exposure: Gain experience across data warehousing, machine learning, cloud technologies, big data, and enterprise analytics solutions.

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Leadership opportunities: Manage cross-functional teams and projects spanning multiple geographies and business units.

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Strategic impact: Contribute to technology initiatives that support business transformation, data-driven decision-making, and innovation. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1