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
- 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.
- Sourcing Strategy: Translate complex technical job requirements into targeted sourcing strategies and build robust talent pipelines for immediate and future needs.
Headhunting & Targeted Search
- Proactive Search: Personally lead targeted headhunting efforts and map talent pools across companies geographies and technology stacks to engage high-caliber passive candidates.
- Relationship Building: Employ creative engagement approaches and foster long-term relationships with niche technical professionals.
Advanced Sourcing & Intelligence
- Digital Sourcing: Utilize LinkedIn Recruiter GitHub Boolean/X-ray search professional communities and digital channels to identify technical talent.
- Market Intelligence: Provide leadership with actionable insights on market trends skills availability compensation standards competitor hiring patterns and talent concentrations.
Stakeholder & Candidate Management
- Strategic Partnership: Partner closely with CTOs CIOs and engineering leaders as a trusted advisor to calibrate requirements and set hiring strategies.
- 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:
- Data & Engineering:
Big Data Data Warehousing Data Architecture Databricks Snowflake ETL/ELT SQL.
- AI & Machine Learning: Machine Learning Deep Learning Generative AI/LLMs NLP Computer Vision MLOps.
- Cloud & Modern Stack: AWS/Azure/GCP Data Lakes/Lakehouse Data Governance.
- Data Science & Analytics: Applied/ML/Decision Scientists Product Analytics Advanced Analytics Business Intelligence.
Key Requirements & Differentiators
- Experience: 68 years of experience in technical recruitment with a proven track record of hiring niche Data AI and Data Science talent.
- Search Expertise: Demonstrated expertise in headhunting passive candidate outreach LinkedIn Recruiter Boolean search and structured market mapping.
- Technical Depth: Ability to differentiate subtle skill sets (e.g. Data Engineer vs. ML Engineer vs. GenAI Specialist) beyond simple keyword matching.
- Network: Strong network within top technology firms AI companies product organizations or specialized consulting practices.
- Soft Skills: Exceptional communication influencing executive presence and stakeholder management capabilities.
- Education: MBA or Postgraduate degree in HR or Business Management.
Required Skills:
Key Requirements & Differentiators Experience: 68 years of experience in technical recruitment with a proven track record of hiring niche Data AI and Data Science talent. Search Expertise: Demonstrated expertise in headhunting passive candidate outreach LinkedIn Recruiter Boolean search and structured market mapping. Technical Depth: Ability to differentiate subtle skill sets (e.g. Data Engineer vs. ML Engineer vs. GenAI Specialist) beyond simple keyword matching. Network: Solid network within top technology firms AI companies product organizations or specialized consulting practices. Soft Skills: Exceptional communication influencing executive presence and stakeholder management capabilities. Education: MBA or Postgraduate degree in HR or Business Management.