Quality Analyst
hace 3 días
ANNOTATION & LABELLING: Transcription, summarization, image and video classification and labeling. ENHANCING LLMs: Prompt engineering, SFT, RLHF, red teaming and adversarial model training, model output ranking. DATA COLLECTION & GENERATION: From institutional languages to remote field audio collection. RELEVANCE & INTENT: Culturally nuanced and aware, ranking, relevance, and evaluation to train models for search, ads, and LLM output.
Want to join our Welo Data team? We bring practical, applied AI expertise to projects. We have both strong academic experience and a deep working knowledge of state-of-the-art AI tools, frameworks, and best practices. Help us elevate our clients' Data at Welo Data.
Role Purpose Owns client-specific quality programs, performance metrics, and escalations while leading team development and cross-functional coordination. Shared accountability for client outcomes and team performance with the Ops Manager. Key Responsibilities
- Set client QA strategies (sampling design, audit methods, acceptance thresholds) and adapt to scope/volume changes.
- Run root-cause analyses; drive CAPA plans with owners, timelines, and effectiveness checks.
- Plan training & certification for raters/annotators and coordinators; track completion and impact.
- Maintain dashboards (throughput, accuracy, productivity, cost) and convert insights into actions.
- Manage client escalations; present options, trade-offs, and recovery paths.
- Standardize SOPs, templates, and checklists; remove bottlenecks.
- Pilot small automations (macros, templates, RPA/API handoffs) with Ops Tech; scale wins.
- Coach P1s and C2–C3 on tools, workflows, and QA craft.
- Ensure compliance/security across data handling and platform access.
- Multi-project planning and stakeholder management.
- Clear client communications and governance cadence participation.
- Strong spreadsheets, PM/task boards, and basic BI; ETL familiarity is a plus.
- Capacity planning with vendors; confident escalation/negotiation.
- Effective in global, distributed teams.
- Near-native English with strong writing and editorial skills.
- Hands-on with generative AI tools (text/voice/video).
- Background in QA testing, rubric design, or AI safety/ethics evaluation.
- Familiarity with data-annotation platforms and model-evaluation tools.
- Ability to interpret code/datasets/workflows at a conceptual level (no coding required).
- Works independently and manages workflows effectively in a remote setup.
- Multilingual ability beyond English.
- Leads quality, training, and performance tracks across several projects; independent within guardrails.
- Shared accountability for client results and team performance with Ops Manager.
- Bachelor's degree or equivalent experience in Business, Operations, Quality, or Data/Engineering.
- 2+ years in quality/ops with hands-on QA and workforce/training coordination.
- 1+ years leading people/pods (formal or informal).
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