Teradata
Website:
teradata.com
Company:
https://www.linkedin.com/company/teradata
Seniority: Mid-Senior level
Industries: Software Development and IT Services and IT Consulting
Job details:
Our Company:
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You’ll Do
Lead high-impact UX research
- Plan, conduct, and synthesize mixed-method research including interviews, usability testing, surveys, diary studies, NPS/CSAT analysis, workshops, concept testing, and prototype evaluations.
- Deliver rapid discovery studies in 1–2 week cycles and deeper strategic studies over 4–12 weeks.
- Translate findings into decision-focused outputs: prioritized user problems, product opportunities, prototype recommendations, success metrics, and risks to validate.
- Partner closely with Product Design, PM, Engineering, Data/Analytics, OCTO Research, and platform teams to shape roadmap direction and measure post-launch impact.
Build research recruiting and participant operations
- Build, segment, and maintain a high-quality research participant panel across priority personas, markets, customer types, product usage patterns, and accessibility needs.
- Create and improve recruiting scripts, screeners, consent flows, invite templates, incentive processes, scheduling workflows, and participant hygiene routines.
- Implement quality controls to reduce poor-fit participants, duplicate participants, AI-assisted screener gaming, no-shows, and recruiting fraud. Modern participant recruitment increasingly requires strong screeners, clear incentives, quality verification, and awareness of AI-enabled participant behavior.
- Track recruiting metrics such as fill rate, response rate, qualification rate, no-show rate, time-to-recruit, cost per engaged participant, and participant quality.
Stand up ResearchOps infrastructure
- Configure and maintain the research repository, including folder structure, taxonomy, tags, templates, saved searches, access controls, and publishing standards. Research repositories should make studies, artifacts, transcripts, insights, and evidence searchable, traceable, reusable, and accessible across product teams.
- Implement a canonical study-ID model and metadata mapping across tools such as Dovetail, Transcend, Pendo, Jira, and related systems.
- Automate and document the research lifecycle from intake → triage → recruiting → scheduling → consent → data capture → synthesis → repository ingest → insight socialization → product follow-through.
- Create SOPs, playbooks, and reusable templates for screeners, moderator guides, consent, incentives, transcription, redaction, synthesis, repository publishing, and stakeholder readouts.
Introduce responsible AI into research workflows
- Define practical AI use cases for research planning, screener drafting, interview-guide generation, transcript cleanup, initial coding, theme clustering, insight summarization, repository search, and reporting. AI is increasingly used in UXR for study planning, screener development, synthesis, summarization, tagging, and refinement, but still requires human review and guardrails.
- Establish standards for human validation of AI-assisted summaries, themes, tags, and recommendations.
- Partner with Legal, Security, Data, and Privacy teams to ensure participant data is handled responsibly, including consent, minimization, redaction, retention, and access controls. India’s Digital Personal Data Protection Act emphasizes notice, consent, lawful processing, data security, and individual rights for digital personal data.
First 15-Month Deliverables
- Deliver 12–20 rapid studies and 4–6 in-depth strategic studies tied to product and platform decisions.
- Launch and scale a vetted participant panel to 1,200+ contacts across priority segments.
- Stand up a fully configured research repository with taxonomy, templates, access controls, and initial studies ingested.
- Launch an intake and triage workflow that supports request routing, scheduling, recruiting, and repository ingest.
- Deliver a canonical study-ID convention and metadata mapping across Dovetail → Transcend → Pendo → Jira.
- Publish a complete SOP library and research playbook for recruiting, consent, incentives, moderation, synthesis, AI use, and insight sharing.
- Produce quarterly research impact reports linking insights to product decisions, features launched, rework avoided, risks reduced, and metric improvements.
What Success Looks Like
- Product teams make faster, more confident decisions using trusted research evidence.
- Recruiting becomes faster, higher-quality, and more predictable.
- Research findings are searchable, reusable, and connected to product outcomes.
- Designers, PMs, and partners improve their research skills through coaching and templates.
- AI improves research efficiency without compromising participant privacy, evidence quality, or human judgment.
Required Qualifications
- 8–12+ years of experience in UX research, product research, ResearchOps, design research, or adjacent customer-insights roles.
- Strong mixed-method research experience across generative and evaluative methods.
- Proven experience building or improving research recruiting, participant panels, screeners, consent flows, and incentive processes.
- Experience with research repositories, taxonomy, metadata, tagging, insight governance, and stakeholder adoption.
- Strong understanding of research ethics, privacy, consent, data minimization, and secure participant-data handling.
- Excellent storytelling, facilitation, synthesis, and executive communication skills.
- Ability to mentor designers, PMs, researchers, interns, and non-researchers in safe and effective research practices.
Preferred Qualifications
- Experience with enterprise SaaS, data platforms, cloud platforms, analytics, developer tools, AI products, or complex B2B workflows.
- Familiarity with tools such as Dovetail, Pendo, Jira, Transcend, Figma/FigJam, Miro, Qualtrics, User Interviews, Respondent, Ethnio, Zoom, Teams, and approved AI assistants.
- Experience connecting qualitative insights with behavioral analytics, product telemetry, experimentation, or product adoption data.
- Experience defining AI standards or workflows for research planning, synthesis, repository management, or reporting.
Why We Think You’ll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement. It is a deep commitment to doing the work to foster an equitable environment that celebrates people for all of who they are.
Teradata invites all identities and backgrounds in the workplace. We work with deliberation and intent to ensure we are cultivating collaboration and inclusivity across our global organization. We are proud to be an equal opportunity and affirmative action employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status.
Click on Apply to know more.