Delivery leadership: Lead the full lifecycle of Data & AI projects-discovery, design, build, deployment, and adoption-across multiple concurrent engagements.
Planning & execution: Develop and maintain detailed project plans, budgets, RAID logs, and resource forecasts; manage scope, timelines, and dependencies using Agile, Waterfall, or hybrid approaches as appropriate.
Stakeholder management: Serve as the primary point of contact for client executives, product owners, and technical leads; clearly communicate progress, risks, trade-offs, and value realization.
Cross-functional coordination: Orchestrate work across data engineers, data scientists, ML engineers, architects, business analysts, and domain SMEs to deliver integrated outcomes.
Industry contextualization: Apply working knowledge of Automotive, Agriculture, and Manufacturing operations (e.g., connected vehicle data, precision agriculture, predictive maintenance, supply-chain analytics) to shape delivery and de-risk execution.
Governance & quality: Enforce delivery standards, model governance, data quality, security, and responsible-AI practices in line with organizational and regulatory requirements.
Commercial accountability: Track financials against forecast, manage change requests, identify upsell opportunities, and ensure margin and utilization targets are met.
Continuous improvement: Run retrospectives, capture lessons learned, and contribute to internal delivery playbooks, estimation models, and capability uplift.

Minimum 5 years of professional project management experience, with a demonstrable track record of delivering Data, Analytics, or AI/ML solutions end-to-end.
Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related discipline. Master's degree or MBA is a plus.
Proven delivery experience across at least two of the following verticals: Automotive, Agriculture, Manufacturing (e.g., IoT/telematics, smart farming, Industry 4.0, MES integration, predictive maintenance, computer vision on the factory floor).
Strong working knowledge of modern data and AI technologies, including cloud data platforms (Azure, AWS, or GCP), data pipelines, MLOps, and at least foundational familiarity with generative AI and LLM-based solutions.
Hands-on experience leading Agile (Scrum/Kanban) and hybrid delivery teams, including distributed and offshore squads.
Excellent stakeholder management skills-comfortable engaging C-level sponsors, plant managers, R&D heads, and technical specialists with equal credibility.
Strong commercial acumen: budget ownership, vendor management, SOW shaping, and change control.
Demonstrated ability to navigate ambiguity, prioritize ruthlessly, and drive outcomes in environments where data maturity varies significantly.
Excellent written and verbal communication skills, including the ability to translate technical concepts for non-technical audiences.

Flexibility, with remote and hybrid work options (country-dependent)
Career advancement, with international mobility and professional development programs
Learning and development, with access to cutting-edge tools, training and industry experts

Senior Project Manager

Key skills