Project Manager

Key Responsibilities :

• Project Leadership : Lead the end-to-end delivery of data science, machine learning, and automation projects, from initial concept and data discovery to final deploymentand iteration.
• Stakeholder & Customer Management: Serve as the primary point of contact forclients and internal stakeholders, translating business requirements into technicalproject plans and managing expectations.
• Scope & Schedule Management : Define project scope, create detailed roadmaps,manage timelines, and control budgets to ensure projects are delivered on scheduleand within financial constraints.
• Team Handling & Mentorship : Guide, support, and mentor a cross-functional teamof data scientists, ML engineers, and data engineers, fostering a highly collaborativeand agile work environment.
• Process & Automation Driver : Identify opportunities and drive the automation of data pipelines, model training, and deployment workflows (MLOps) to improve efficiency, scalability, and speed-to-market.
• Risk Management : Proactively identify and mitigate risks related to data quality, model performance, and project dependencies, ensuring smooth execution.

Qualifications and Skills :

• Experience: Proven experience in project management, specifically handling complex data science, AI/ML, or technical automation projects.
• Agile Proficiency: Strong understanding and practical experience with agile methodologies to manage iterative and research-oriented projects.
• Communication: Exceptional communication and interpersonal skills, with the ability to articulate complex technical concepts to non-technical audiences.

Technical Acumen (Bonus) :

• Solid understanding of the machine learning project lifecycle.
• Familiarity with core data science tools and languages (e.g., Python, SQL).
• Knowledge of major cloud platforms (AWS, Azure, GCP) and their AI/ML services is a significant plus.