Job Title:
Deputy Manager / Manager ? Taxonomy Operations
Location:
Noida
Role Overview:
Lead role ? Taxonomy Operations
You will own the roadmap for taxonomy enrichment, identify gaps, and develop scalable and automated strategies to ensure high coverage, accuracy, and completeness across the platform.
Key Responsibilities:
Platform Health & Taxonomy Coverage
- Own and manage master taxonomies across key entities (colleges, companies, skills, designations, etc.).
- Ensure comprehensive coverage and alignment of taxonomy with industry standards and platform needs.
- Monitor and improve
taxonomy fill rates
across the job seeker funnel. - Identify and reduce
free-text long tail entries
by driving structured value adoption.
Data Quality & User Behavior Insights
- Analyze user input patterns to identify areas where structured selections are underutilized.
- Design interventions to
nudge job seekers
towards selecting from taxonomy masters. - Collaborate with product and UX teams to improve UI/UX for better taxonomy adoption.
Automation & Operational Scaling
- Develop
automated pipelines
for deduplication, clustering, synonym resolution, and enrichment. - Ensure regular feedback is shared with the data science team for improving the prediction
- Build tools and dashboards to
empower taxonomy analysts
with faster and more accurate workflows.
Cross-Functional Collaboration
- Work closely with product, engineering, data science, and operations teams to integrate taxonomy logic across the platform.
- Partner with marketing and B2B teams to ensure taxonomy supports business needs and campaigns.
Team Leadership & Strategy
- Build, lead, and mentor a team of taxonomy analysts and specialists.
- Define OKRs and drive execution against operational targets and strategic goals.
Success Metrics (KPIs):
Fill Rate Improvement
: % increase in structured field selection by job seekers (target: +15?20% YoY).Longtail Reduction
: % reduction in unique free-text values across key entities (target: -30% YoY).Coverage Ratio
: % of platform-wide records successfully mapped to taxonomy masters (target: >95%).Automation Efficiency
: % of taxonomy tasks automated vs. manual (target: >70% automated).Turnaround Time (TAT)
: Reduction in time to resolve taxonomy gaps or integrate new terms.Precision/Recall
in normalization and classification pipelines (>95%).
Required Skills and Experience:
- 7?10 years of experience in taxonomy/ontology management, data operations, or structured data systems.
- Experience working with recruitment/job platforms, e-commerce, or content-heavy platforms preferred.
- Strong analytical mindset with hands-on experience in
data cleaning, clustering, and classification
. - Knowledge in Open AI, SQL, Python, or relevant scripting languages.
- Strong project management and stakeholder collaboration skills.
- Demonstrated ability to scale systems and teams.
