Data Science Engineer

Responsibilities

• Handle competing priorities and manage stakeholder expectation through realistic negotiation.
• Establish and prioritize the team backlog in collaboration with the team.
• Participate in Program Increment planning events with technical and business stakeholders and set expectations for delivery of new functionalities.
• Participate in system demos at the end of the iteration and provide story/feature acceptance per the pre-agreed acceptance criteria.
• Engage in scaled agile practices and coordinate with other POs as needed to promote cross-team alignment around product roadmaps and dependencies.

Required Skills

• Excellent verbal/written communication, collaboration, analytical and presentation skills.
• Good analytical skills with the ability to understand data integration points, process workflows from an end to end perspective.
• Ability to work with value stream architects, technical SMEs to come up with solutions and ensure that solution meets business needs.
• Ability to analyze, map, translate technical changes to business value and communicate to various stakeholders.

Required Experience

• Experience with Financial Industry – preference in the Real Asset business platforms is a plus.
• Experience leveraging analytics to identify opportunities to improve customer experience and product performance KPIs.
• Deep Experience soliciting requirements and breaking them down into digestible user stories and acceptance criteria.
• Experience as a Product Owner or Scrum Master in an Agile environment. Certification is a plus.
• Experience in the use of agile software productivity tools (i.e. JIRA).

Education Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering or a closely related field.