Lead Talent Acquisition Specialist
Koantek · koantek.com
MumbaiLead / Manager
Straight from the company’s own careers site.
The job in short
Talent acquisition.
Machine learningGenerative AIMLOpsData scienceRecruitment
Details
- Found
- 30 d ago · posted 2026-09-18
- Location
- Mumbai, Maharashtra
Full description
Role Overview
We are looking for a strategic, research-driven Senior Talent Acquisition Specialist to drive targeted end-to-end recruitment for niche Data, AI, and Data Science roles. This role requires deep technical recruitment expertise, proactive headhunting, and talent mapping to engage passive candidates in non-volume hiring scenarios.
Key Responsibilities
End-to-End Talent Acquisition
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Full Lifecycle Hiring: Manage end-to-end recruitment across Data Engineering, Data Science, Machine Learning, Generative AI, MLOps, Data Architecture, Cloud Data, and Advanced Analytics.
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Sourcing Strategy: Translate complex technical job requirements into targeted sourcing strategies and build robust talent pipelines for immediate and future needs.
Headhunting & Targeted Search
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Proactive Search: Personally lead targeted headhunting efforts and map talent pools across companies, geographies, and technology stacks to engage high-caliber passive candidates.
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Relationship Building: Employ creative engagement approaches and foster long-term relationships with niche technical professionals.
Advanced Sourcing & Intelligence
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Digital Sourcing: Utilize LinkedIn Recruiter, GitHub, Boolean/X-ray search, professional communities, and digital channels to identify technical talent.
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Market Intelligence: Provide leadership with actionable insights on market trends, skills availability, compensation standards, competitor hiring patterns, and talent concentrations.
Stakeholder & Candidate Management
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Strategic Partnership: Partner closely with CTOs, CIOs, and engineering leaders as a trusted advisor to calibrate requirements and set hiring strategies.
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Offer Management: Articulate complex technology opportunities to candidates and effectively manage end-to-end offer discussions and negotiations.
Technical Focus Areas
Candidates must possess functional familiarity across the following technical domains to conduct intelligent screenings:
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Data & Engineering: Big Data, Data Warehousing, Data Architecture, Databricks, Snowflake, ETL/ELT, SQL.
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AI & Machine Learning: Machine Learning, Deep Learning, Generative AI/LLMs, NLP, Computer Vision, MLOps.
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Cloud & Modern Stack: AWS/Azure/GCP, Data Lakes/Lakehouse, Data Governance.
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Data Science & Analytics: Applied/ML/Decision Scientists, Product Analytics, Advanced Analytics, Business Intelligence.
Key Requirements & Differentiators
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Experience: 6–8 years of experience in technical recruitment with a proven track record of hiring niche Data, AI, and Data Science talent.
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Search Expertise: Demonstrated expertise in headhunting, passive candidate outreach, LinkedIn Recruiter, Boolean search, and structured market mapping.
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Technical Depth: Ability to differentiate subtle skill sets (e.g., Data Engineer vs. ML Engineer vs. GenAI Specialist) beyond simple keyword matching.
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Network: Strong network within top technology firms, AI companies, product organizations, or specialized consulting practices.
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Soft Skills: Exceptional communication, influencing, executive presence, and stakeholder management capabilities.
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Education: MBA or Postgraduate degree in HR or Business Management.
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