About the Role
Labelbox’s mission is to build the best products for humans to advance artificial intelligence. As a Workforce Project Manager, you will work across engineering, customer, and data labeling teams to create highly accurate datasets. This is a unique, cross-functional position where you will be the go-to person for successful project outcomes for customers.
Your Day to Day
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Create a partner success model with partner QBRs, feature roadmap alignment and growth strategy with workforce partners.
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Create an operating model that is adopted repeatedly across a highly scaled number of workforce partners.
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Work cross-functionally with Product Management, Sales, and leadership to align and identity new workforce partnership opportunities.
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Help customers build production-grade data labeling pipelines.
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Track and analyze metrics to deliver remarkable customer service. Accuracy, precision, time-to-delivery, speed, and cost are the key metrics for a successful project.
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Lead large-scale data operations projects between customers and workforce teams.
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Assess and manage data labeling workforce performance to help them deliver the best results.
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Continuously improve quality and throughput of our data labeling services.
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Develop policies, guidelines, and workflows pertaining to data management and labeling services.
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Set up processes for data driven decision making for BPO matchmaking, BPO quality rating, and BPO customer rating.
About You
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Experience with establishing scalable and repeatable operating models with BPOs.
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Proactively find ways to improve and scale up workforce efforts.
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A passion for data and quality.
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Strong analysis and troubleshooting skills.
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An ability to navigate and advise on efforts related to complex customer requests or projects, gathering additional human resources for assistance if needed.
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A strong motivation to work closely with customers to create the best possible experiences with Labelbox.
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Assertive, positive, and effective communication skills in English – both written and verbal – with considerable attention to detail and the ability to present and influence.
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Demonstrated problem-solving ability, particularly in complex technical situations.
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Relevant professional experience in data labeling for ML.
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Experience building and/or QAing datasets.
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At least 5 years of experience with analytical software such as Excel.
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Vendor management experience.
Nice to Have
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Experience working with Language or Labeling/Linguistics.
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Experience working on computer vision use cases.
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Experience working as a Quality Assurance Analyst (QAA).
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Experience scoping and developing ontologies and taxonomies.
