Coalition

Senior Manager, Machine Learning (Data Operations)

Coalition$134K — $200K *
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in ML data operations, data labeling, or related field
  • Deep understanding of annotation quality frameworks
  • Direct experience managing labeling platforms
  • Track record managing outsourced labeling vendors
  • Familiarity with common ML labeling tasks
  • Comfortable working in Python and SQL
  • Strong opinions on labeling quality

Responsibilities

  • Define annotation guidelines and establish quality frameworks
  • Serve as primary user for Label Studio and define project needs
  • Partner with ML and product teams to translate requirements into tasks
  • Source and manage external labeling vendors and set quality SLAs
  • Define and track operational metrics for continuous improvement

Benefits

  • 100% medical, dental and vision coverage
  • Flexible PTO policy
  • Annual home office stipend and WeWork access
  • Mental & physical health wellness programs
  • Competitive compensation and opportunity for advancement
Full Job Description
About the role

Coalition's machine learning models are only as good as the data they're trained on. This role exists to make sure that data is right.

You'll own labeling quality and methodology across Coalition - designing annotation tasks, defining quality frameworks, and ensuring every labeled dataset meets the standard required to ship production ML models. You'll manage our labeling platform (Label Studio), work directly with ML and product teams to structure labeling programs, and oversee outsourced labeling vendors to hit quality and throughput targets.

This role reports to the Chief Product Officer and sits at the intersection of product, ML, and operations. You won't manage internal labelers - all annotation work is outsourced - but you will be the single point of accountability for whether Coalition's labeled data is accurate, consistent, and fit for purpose.
Responsibilities
  • Labeling quality & methodology: Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program. Establish gold standard datasets, inter-annotator agreement (IAA) targets, and audit sampling processes. Identify and remediate mislabeled data in existing datasets.
  • Platform & tooling: Serve as the primary user and requirements driver for Label Studio - defining project configuration needs, workflow designs, pre-labeling pipeline requirements, and integration points with ML infrastructure. Partner with the data engineering team that builds and maintains the platform.
  • Cross-functional partnership: Work with ML engineers, data scientists, and product managers to translate model requirements into well-structured labeling tasks. Challenge teams on task design when labeling instructions are ambiguous or likely to produce unreliable labels.
  • Vendor management: Source, onboard, and manage external labeling vendors and BPOs in coordination with Coalition's operations team. Set quality SLAs, run calibration sessions, and manage feedback loops to labelers. Hold vendors accountable to accuracy, not just throughput.
  • Measurement & improvement: Define and track operational metrics - label accuracy, IAA scores, cost per label, turnaround time - and use them to drive continuous improvement. Identify opportunities for active learning, model-assisted labeling, and pre-annotation to reduce cost without sacrificing quality.
Skills and Qualifications
  • 5+ years in ML data operations, data labeling, or a related field (ML engineering, data science, or data engineering with heavy labeling exposure)
  • Deep understanding of annotation quality frameworks: IAA, consensus labeling, gold standard evaluation, error taxonomy, and calibration workflows
  • Direct experience managing labeling platforms (Label Studio strongly preferred; Scale AI, Labelbox, Prodigy, or similar acceptable)
  • Track record managing outsourced labeling vendors or BPOs for ML data production
  • Familiarity with common ML labeling tasks: text classification, NER, document extraction, intent detection
  • Comfortable working in Python and SQL; bonus if you've built tooling around labeling workflows or quality measurement
  • Strong opinions on what makes labeled data good or bad, and the willingness to push back when it's bad
  • Experience in insurance, cybersecurity, or fintech is a plus but not required
Compensation

Our compensation reflects the cost of labor across several US geographic markets. The US base salary for this position ranges from $134,400/year in our lowest geographic market up to $200,000/year in our highest geographic market. Consistent with applicable laws, an employee's pay within this range is based on a number of factors, which include but are not limited to relevant education, skills, job-related knowledge, qualifications, work experience, credentials, and/or geographic location. Your recruiter can share more on target salary for your location during the interview process. Coalition, Inc. reserves the right to modify this range as needed.
Perks
  • 100% medical, dental and vision coverage
  • Flexible PTO policy
  • Annual home office stipend and WeWork access
  • Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more)!
  • Competitive compensation and opportunity for advancement

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About Coalition

Coalition is a UK-based financial technology company that provides risk management and analytics solutions to financial institutions. The company was founded in 2008 and has since grown to become a leading provider of risk management software, with clients including some of the world's largest banks and asset managers. Coalition's technology platform allows financial institutions to monitor and manage their risk exposure in real-time, providing insights into market trends and potential risks. The company has received numerous awards for its innovative approach to risk management, including the Risk Management Technology Provider of the Year at the Risk Awards in 2019.
Learn more about Coalition
Size
200 employees
Industry
Founded
2017

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