
Senior Project Manager
Posted 6 days ago

Posted 6 days ago
This is a fully remote position, open to applicants in India.
• Leadership in delivery: Oversee the complete lifecycle of Data & AI projects, including discovery, design, development, deployment, and adoption across various simultaneous engagements.
• Planning and execution: Create and uphold comprehensive project plans, budgets, RAID logs, and resource forecasts; manage scope, timelines, and dependencies utilizing Agile, Waterfall, or hybrid methodologies as needed.
• Stakeholder engagement: Act as the main contact for client executives, product owners, and technical leads; effectively communicate updates, risks, trade-offs, and value realization.
• Cross-functional collaboration: Coordinate efforts among data engineers, data scientists, ML engineers, architects, business analysts, and domain subject matter experts to achieve integrated outcomes.
• Industry expertise: Utilize practical knowledge of Automotive, Agriculture, and Manufacturing operations (such as connected vehicle data, precision agriculture, predictive maintenance, and supply-chain analytics) to inform delivery and mitigate execution risks.
• Governance and quality assurance: Uphold delivery standards, model governance, data quality, security, and responsible AI practices in accordance with organizational and regulatory standards.
• Financial accountability: Monitor financial performance against forecasts, manage change requests, identify upsell opportunities, and ensure margin and utilization targets are achieved.
• Continuous enhancement: Conduct retrospectives, document lessons learned, and contribute to internal delivery playbooks, estimation frameworks, and capability improvements.
• At least 5 years of professional project management experience, demonstrating a successful track record in delivering Data, Analytics, or AI/ML solutions from inception to completion.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related field; a Master's degree or MBA is an advantage.
• Proven experience in delivery across a minimum of two of the following sectors: Automotive, Agriculture, Manufacturing (for example, IoT/telematics, smart farming, Industry 4.0, MES integration, predictive maintenance, computer vision on the factory floor).
• Strong expertise in modern data and AI technologies, including cloud data platforms (Azure, AWS, or GCP), data pipelines, MLOps, and at least a foundational understanding of generative AI and LLM-based solutions.
• Practical experience in leading Agile (Scrum/Kanban) and hybrid delivery teams, including managing distributed and offshore squads.
• Exceptional stakeholder management abilities—capable of engaging C-level sponsors, plant managers, R&D leaders, and technical experts with equal credibility.
• Strong commercial insight: budget management, vendor oversight, SOW development, and change management.
• Proven capability to navigate uncertainty, prioritize effectively, and drive results in environments with varying levels of data maturity.
• Outstanding written and verbal communication skills, including the capacity to explain technical concepts to non-technical audiences.
• Flexibility through remote and hybrid work options (dependent on country).
• Opportunities for career progression, including international mobility and professional development programs.
• Access to learning and development resources, featuring cutting-edge tools, training, and industry experts.
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