Merchant Operations and Quality Lead at Mecka in New York

Job description

• Application
• Our dataset is valuable only to the extent that it is authentic, complete, and operationally usable across all machine learning and operational workflows. We maintain and continuously evaluate data quality through a rigorous hybrid approach combining models with verification.
• In this role, you will build, scale, and lead our global review operations organization, taking full operational accountability for critical quality and performance metrics including review coverage, multi-pass accuracy, reviewer throughput, SLA compliance, and unit economics/cost management. You will establish robust, continuous feedback loops connecting local merchants, external BPO partners, field capture teams, and executive management to drive dataset standards. Serving as the operational partner to our quality engineering and machine learning teams, you will ensure our operational insights directly inform, calibrate, and improve automated models, annotation workflows, and field capture guidelines.

Responsibilities

• Team leadership: Lead, structure, and scale a high-volume review and approval organization encompassing internal teams and vendor partners. Hire, develop, and coach operational team leads, establish clear performance management frameworks, and manage headcount, shift scheduling, and operational budgets to optimize unit economics.
• Coverage and accuracy: Take end-to-end ownership of review coverage, SLA adherence, reviewer throughput, and multi-tier accuracy. Design and execute regular calibration sessions, inter-annotator agreement audits, and QA reporting to enforce a unified quality standard across all global locations.
• Merchant quality: Define and enforce merchant approval workflows, automated pre-payout verification checks, and merchant compliance standards. Publish weekly quality scorecards and establish structured feedback loops with sales, account management, and business development teams with strict service level agreements for resolution.
• Engineering partnership: Partner closely with data engineering, product, and AI research teams to embed our evaluation insights into model training. Define active learning edge cases, continuously refine automated rule checks, and report operational quality metrics and cost models to executive leadership on a weekly cadence.
• Integrity: Lead the operational protocol and response framework when fraud, data tampering, or platform integrity issues are detected. Collaborate with engineering, legal, and finance to investigate root causes, mitigate risk, enforce merchant suspensions, and prevent future recurring vulnerabilities.

Requirements

• Experience: 5 to 8+ years of progressive operational leadership experience managing large-scale review, merchant, trust and safety, community, or data quality operations in high-growth environments.
• Quality programmes: Demonstrated track record of architecting comprehensive quality control frameworks from scratch, including balanced scorecards, statistical sampling techniques, cross-team calibration sessions, and targeted coaching loops.
• Analytical skills: Exceptional analytical acumen with proficiency in building operational dashboards, writing SQL queries, modeling unit economics, and communicating complex statistical performance data effectively with AI/ML engineers.
• Industry: Direct experience in merchant operations, content moderation, or onboarding at a top-tier marketplace, hyper-local logistics, or delivery platform operating across Southeast Asia or international markets.
• Vendors: Hands-on experience procuring, negotiating, and managing third-party BPO vendor relationships, setting up vendor SLAs, and running quarterly business reviews
• Data quality: Deep familiarity with computer vision data collection, video stream evaluation, bounding-box/semantic segmentation annotation pipelines, or synthetic data training setups.

Skills

Required

• Operational leadership
• Quality control framework design
• Statistical sampling
• Cross-team calibration
• Coaching
• Analytical skills
• Dashboard building
• SQL
• Unit economics modeling
• Communication with AI/ML engineers

Preferred

• Merchant operations
• Content moderation
• Onboarding
• BPO vendor management
• Vendor SLA setup
• Computer vision data collection
• Video stream evaluation
• Synthetic data training setups

Benefits

• Our Compensation Philosophy
• Mecka uses industry benchmark data to establish compensation bands for all roles. The salary range listed for a position reflects the expected total wage range for the role. This includes base salary and on-target incentives, where applicable and may span multiple career levels. Final compensation is determined during the interview process based on factors such as experience, skills, scope, and role level. In addition to base salary, total rewards may include equity, health and wellness benefits, and other company programs. Full details will be shared during the interview process.
• Compensation is region specific and will potentially be different based on the location where the candidate is hired.