New York, NY, USA
1 day ago
Product manager - Machine Learning Center
You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients.
As a Product Manager in the Machine Learning Center, you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. As a core leader, you are responsible for acting as the voice of the customer and developing profitable products that provide customer value. Utilizing your deep understanding of how to get a product off the ground, you guide the successful launch of products, gather crucial feedback, and ensure top-tier client experiences. With a strong commitment to scalability, resiliency, and stability, you collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations. Excellence, will be responsible for understanding client needs, designing solutions to translate these needs into workflows aligned with our strategic vision, managing overall delivery, and overseeing the go-to-market strategy for the product. You will collaborate with data scientists, engineers, market experts, annotators, and project managers to curate the feature vision, strategy, and execution.
 Job responsibilitiesCreate data flow diagrams, customer journey mapping, etc to clearly map out the requirements and user journey end-to-end.Build robust product requirement documents and set clear scope, test strategies and execution plans.Work very closely with the data scientists and engineers to brainstorm ideas and solve business problems.Design metrics and KPIs to measure your feature/product success, and make sure your team and your stakeholders understand how you are measuring your product success.Test new features, approve launches and engage stakeholders for an early preview.Design and develop launch/roadshow contents, and work with the stakeholders to create platforms to showcase valuable new features.Collect user testimonials and feedback on regular basis and will iterate the product to create incremental business value.Provide clients with a clear vision and communicate your execution strategy through a well-defined roadmap Required qualifications, capabilities, and skills5+ years of experience or equivalent expertise in product management or a relevant domain areaAdvanced knowledge of the product development life cycle, design, and data analyticsProven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value managementPassion for market instruments and possess strong knowledge of various asset classes, operations, and the instrument life cycle.Experience in cloud computing and architecture, ML platform processes, and tools spanning data ingestion, data engineering, data quality, data orchestration, end-to-end infrastructure, usage/consumption, and data privacy considerations and governance.Experience working on projects involving the ML development lifecycle (MDLC), including annotation, model training, model serving, scoring, pre/post-processing, productionization, and feedback capture.Demonstrate, take initiative and proactive hands-on solutions-orientated approach to achieving team goals. Strive and inspire other team members to commit fully to the team's objectives, and contribute to wherever needed to drive results.Ability to convert ambiguous needs into scalable business solutions. Your solutions are driven by logic, reason, and empirical observations.Preferred qualifications, capabilities, and skillsDemonstrated prior experience working in a highly matrixed, complex organizationThorough understanding of Machine learning and how to approach to building a business development planDemonstrated ability to market products and collaborate amongst customers, stakeholders, and different levels of managementDemonstrated ability to explain machine learning governance


 


 
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