Senior Technical Project Manager (Data / AI)

What you’ll Do:

• Manage resource allocation, project scope, roles and responsibilities and project timeline
• Ensure that all projects are delivered on-time, within scope and within budget
• Assist in the definition of project scope and objectives, involving all relevant stakeholders and ensuring technical feasibility
• Manage changes to the project scope, project schedule and project costs using appropriate verification techniques
• Perform risk management to minimize project risks
• Facilitate collaboration between Data Scientists, ML Engineers, Engineers, and Business Stakeholders 
• Translate business problems into technical data requirements and maintain comprehensive project documentation
• Act as a translator between technical data metrics (e.g., F1 Score, RMSE) and business success metrics.  
• Resolve issues throughout the project lifecycle and provide project updates on a consistent basis to various stakeholders about strategy, adjustments, and progress

What you’ll Need: 

• Bachelor or Master’s degree in Computer Science, Computer Engineer, MIS or related field
• At least 5 years of experience in the role of Business / System Analyst / Data Scientist  or a related Technical Product role.
• Proficiency in SQL for data exploration and experience with visualization / dashboard tools.
• Experience managing data or software development projects, with an understanding of the iterative nature of model development
• Highly effective in communicating with technical and non-technical stakeholders with the ability to build and foster working relationships
• Problem-solving skills with the ability to identify issues, analyze root causes, and implement effective solutions.
• Adaptability to handle changes in project scope, requirements, or resources.
• Strong project management, Leadership, Organizational and Multitasking skills
• Ability to manage expectations regarding the uncertainty of R&D outcomes (e.g., when a model fails to meet accuracy targets)
• Ability to work in a dynamic environment and good discipline in risk control to achieve a high standard in a highly regulated environment
• Fluent in English

It’d be Great if you have: (If any) 

• Knowledge of hypothesis testing for experiment planning and decision making
• Familiarity with common data and software development processes and technologies (REST APIs, microservices, data pipelines, CI/CD processes, MLOps workflows, and data project life cycle)
• Hands-on experience with Agile development specifically adapted for Data Science 
• Familiarity with Jira and Confluence.