Sr. Data Research Analyst II
Elsevier · Chennai · onsite · Posted 1d ago
Undisclosed7–12 yrsfulltimeSourced from
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About this role
Senior Data Research Analyst II
Job Summary
Responsibilities
Requirements
Technical Skills
Project Management Execution
Communication Stakeholder Skills
Education Experience
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Job Summary
As a Data Discovery and Enrichment Expert II, you will operate at the intersection of data, AI, and domain knowledge. You will take ownership of complex data initiatives end-to-end, contribute to shaping how the team leverages AI and data science methods, and work closely with product and customer stakeholders to drive meaningful outcomes. This role is for someone with an execution mindset who thrives on turning ambiguous problems into structured, scalable solutions.
Responsibilities
- Data AI-Driven Discovery: Lead complex data discovery, enrichment, and curation initiatives with a high degree of autonomy
- Data AI-Driven Discovery: Apply data science techniques and AI/ML tools to improve the quality, coverage, and scalability of data assets
- Data AI-Driven Discovery: Design and implement intelligent workflows for source evaluation, entity resolution, and information extraction
- Data AI-Driven Discovery: Develop and maintain taxonomies, ontologies, and knowledge graphs that power downstream products
- Data AI-Driven Discovery: Evaluate and adopt emerging AI tooling relevant to data enrichment and research intelligence
- Product Customer Collaboration: Partner with product managers to translate data insights into product features and improvements
- Product Customer Collaboration: Engage directly with customers and internal stakeholders to understand data needs and validate solutions
- Product Customer Collaboration: Contribute to the product roadmap by identifying data-driven opportunities for domain growth
- Product Customer Collaboration: Communicate findings, recommendations, and data strategies clearly to both technical and non-technical audiences
- Project Execution Team Leadership: Own the end-to-end delivery of data projects, from scoping and planning through execution and review
- Project Execution Team Leadership: Define and drive policies, procedures, and quality standards across the DDE team
- Project Execution Team Leadership: Mentor and support junior team members, providing technical guidance and performance feedback
- Project Execution Team Leadership: Identify and close process gaps; champion a culture of continuous improvement and execution excellence
- Project Execution Team Leadership: Work within agile or project management frameworks to deliver reliably on commitments
Requirements
Technical Skills
- Strong analytical skills with the ability to work with large, complex, and multi-source datasets
- Working knowledge of AI and machine learning concepts, entity extraction, and classification
- Data science skills: ability to prototype, analyse, and iterate on data pipelines and enrichment models
- Familiarity with relevant databases, data tools, and curation platforms
- Experience creating and maintaining taxonomies, controlled vocabularies, or ontologies
- Track record of applying QA standards rigorously and improving them over time
Project Management Execution
- Proven ability to manage multiple priorities and deliver complex projects on time
- Experience with agile methodologies or structured project management approaches
- Execution-oriented: comfortable moving from strategy to delivery with minimal oversight
- Strong problem-solving skills; able to collect data, identify root causes, and act decisively.
Communication Stakeholder Skills
- Excellent written and verbal communication skills; able to adapt style for different audiences
- Confident engaging with customers, product teams, and senior stakeholders
- Ability to translate complex data concepts into clear business language
- Collaborative team player who also takes individual ownership
Education Experience
- MS degree (or equivalent) in a quantitative, information, or research-related field, with 7+ years of relevant experience. Experience in academic publishing, research intelligence, or bibliographic data is a strong advantage.
- We particularly welcome candidates whose background spans data science and a domain-adjacent field (e.g. research analytics, information science, knowledge management), and who are motivated to grow into product and customer-facing responsibilities.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
Agileanalytical thinkingGroup Life Insurancedata enrichmentclassificationDownstreamAnalyticsBankingData ResearchFinancial SecurityHealthcareCommunication SkillsData PipelineData ScienceArtificial Intelligence
About Elsevier
Elsevier
Printing & Publishing
1.6k+
employees
1880
146 years old
Amsterdam, North Holland
NL
₹16.1L PA avg
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As a global leader in information and analytics, Elsevier helps researchers and healthcare professionals advance science and improve health outcomes
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