• Support development of PDS sourcing strategies, including contractor and subcontractor categories • Assist end-to-end sourcing processes: supplier identification, RFP/RFQ development, bid analysis • Build and manage relationships with key PDS suppliers • Conduct periodic market trend analyses and present findings • Prepare sourcing reports and stakeholder updates

• Manage and mentor IT operations team member(s) • Own and grow AWS environment • Design and maintain automated CI/CD pipelines • Build operational maturity through documentation and procedures • Partner with engineering teams for reliable deployments • Lead incident response and implement preventive measures

• Take complete ownership of the business unit’s success. • Develop and execute strategy and tactics for all aspects of our fleet program. • Leadership requirement to lead the team of supervisors and drivers in the field including scheduling, dispatching, and delivering on specific client response service levels. • Be responsible for the fleet but also car leases as well as managing all aspects of the vehicles including leases, gasoline, service, and insurance requirements. • Define standard operating procedures to effectively manage repairs and maintenance. • Track and report operational performance, strategic capital, and operating expenses. • Creation and implementation of management plan to track and manage operating expenses, asset purchases, fuel cost and ongoing maintenance. • Serve as primary liaison for compliance reviews and audits. • Regular reporting to leadership to communicate and mitigate any enterprise level risks. • Implement safety management controls. • Foster a People First culture centered around wellbeing and safety.

Role Description 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. 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. Benefits - 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