About the Role

The Staff Qualitative Researcher is Superbet's most senior practitioner of human-centred inquiry. This is a hands-on, high-output IC role. You are the person who knows how to get to the truth of a user's experience: their mental models, their anxieties, their unspoken expectations, their moments of delight and frustration.

You will lead qualitative research across the most strategically important and ambiguous product questions Superbet faces - from understanding how new markets experience sports for the first time, to uncovering the emotional dynamics of live in-play gambling, to defining what responsible gaming actually feels like from a user's perspective. You will work closely with the Principal Quant Researcher and the Research Manager to ensure qualitative and quantitative evidence are always richer together than apart.

You bring methodological mastery, creative curiosity, and the kind of presence that makes participants forget they're being observed and leaders believe you shape company wide narratives. You also bring a future positive mindset: you are actively integrating AI tools into your workflow to do more, faster, without sacrificing the depth that makes qual irreplaceable. You know when AI is helpful and when it is not and can help junior researchers make decisions around when to use them. 

What You Will Own

Deep Qualitative Research Execution

• Design and independently execute complex, multi-method qualitative research programmes spanning generative discovery, concept exploration, and evaluative depth - not just individual studies but longitudinal programmes of inquiry.
• Lead the most high-stakes and ambiguous research briefs: new market entry, new product category launches, trust and safety research, responsible gambling insights, and strategic bets where the organisation has the least existing evidence.
• Operate the full qualitative toolkit with mastery: semi-structured and unstructured in-depth interviews, contextual inquiry and ethnographic observation, diary studies and longitudinal panels, participatory design workshops, focus groups, co-creation sessions, and remote moderated/unmoderated studies.
• You have deep expertise in mental models, perception, jobs to be done and combining them to paint a rich psychological and workflow design. 
• Own recruitment strategy end-to-end: define screeners, work with research ops and vendors, build proprietary panels where needed, and ensure participant samples are representative of the diversity of Superbet's user base across markets.
• Produce analysis that goes beyond surface themes: you apply systematic coding, grounded theory approaches, interpretive phenomenological analysis, or jobs-to-be-done frameworks -  selecting the analytical lens that fits the question, not the one that's familiar.
• You inspire product teams to take action and drive progress. You can handle different levels of exposure to research within the company and convert colleagues to champions. 

AI-Enhanced Qualitative Workflows

• Lead the integration of AI tooling into Superbet's qualitative research practice - not as a replacement for human interpretation but as a force multiplier that increases throughput and analytical depth.
• Deploy LLM-assisted transcript analysis pipelines that handle first-pass thematic coding, anomaly flagging, and cross-participant pattern detection - freeing analyst time for higher-order interpretation.
• Use AI tools for rapid synthesis across large corpora of qual data: customer feedback, support tickets, app reviews, social listening, and interview transcripts - triangulating signals that would otherwise require weeks of manual work.
• Critically evaluate the output of AI-assisted analysis for bias, hallucination, and over-compression - maintaining methodological integrity while embracing efficiency.
• Build workflows and documentation that allow the broader team to use AI-assisted qual tools responsibly, and run training sessions that upskill colleagues on both the power and the limits of these tools.

Strategic Insight Generation & Storytelling

• Translate raw qualitative data into insight frameworks that have a life beyond the single study: mental model maps, user need taxonomies, experience principles, and behavioural archetypes that inform multiple product teams over multiple quarters.
• Craft research deliverables that move people — not slide decks of quotes, but evidence-driven narratives that make stakeholders genuinely see the world through the user's eyes.
• Partner with the Principal Quant Researcher to design mixed-methods programmes where qual findings generate hypotheses that quant can test at scale, and where quant anomalies trigger qual investigation.
• Present research to senior and executive stakeholders with confidence and authority — you know how to hold the room, handle pushback on findings, and advocate for the user even when their experience is inconvenient for the business.
• Maintain a living qualitative insights repository: tag and cross-reference findings so that past research informs present decisions and the organisation's qualitative knowledge compounds over time.

Research Quality, Standards & Community

• Set the qualitative methodological bar for the research team: review study designs, discussion guides, and analysis from junior and mid-level researchers - providing specific, developmental feedback that elevates their craft.
• Develop and maintain qualitative research standards documentation: best practices for moderation, coding, synthesis, and reporting that are practical, not theoretical.
• Act as a qualitative research community builder within Superbet: run internal workshops, share cutting-edge methods from the field, and make qualitative research legible and valued by non-research partners.
• Identify opportunities to democratise qualitative methods across Product and Design teams, building guardrails and templates that enable safe self-serve research without compromising rigour.

What We Are Looking For

Essential Experience

• 8+ years of UX research experience with a clear depth specialisation in qualitative methods -  ideally with experience in both generative and evaluative contexts across the full product development lifecycle.
• Mastery of qualitative data collection: exceptional moderation skills across IDIs, focus groups, diary studies, ethnographic observation, and co-design facilitation. You are comfortable in the field, in a lab, and on a video call.
• Deep qualitative analysis expertise: systematic thematic analysis, grounded theory, affinity diagramming at scale, IPA, and the judgment to know when interpretive depth is needed versus surface-level synthesis.
• Strong mixed-methods fluency: experience designing studies that integrate qual and quant, and the ability to have a credible technical conversation with quantitative researchers about their methodology.
• Demonstrated experience using AI tools in qualitative workflows - not just awareness, but real implementation with critical assessment of quality and validity.
• A track record of qualitative research that influenced major product or strategy decisions, with specific examples you can speak to in depth.
• Experience working across multiple markets or cultural contexts - essential given Superbet's multi-country footprint.

Skills & Mindset

• World-class moderator: You have a gift for putting participants at ease and creating the conditions where genuine, unguarded truth emerges. You know when to probe, when to wait, and when to redirect.
• Interpretive depth: You go beyond what users say to understand what they mean — and you can defend your interpretations with analytical rigour, not just instinct.
• AI-enhanced, not AI-dependent: You use AI to go faster and deeper, but your analytical judgement is irreplaceable and you know it. You apply AI tools critically, not uncritically.
• Generative thinker: You don't just answer the research question - you reframe it when necessary, spot adjacent insights the brief didn't ask for, and bring back richer evidence than expected.
• Empathy with edge: You care deeply about users and can advocate for them powerfully - but you're not naive. You understand the commercial context and know how to make the business case for user-centred decisions.
• Cultural intelligence: You are sensitive to the ways that culture shapes how people talk about their experiences, and you adjust your research approach accordingly.
• Org Mover - Your research is not theory alone, you know how to make things tangible, bite sized and move people and work forward. 
• Embrace difficult conversations - Driving research impact is as much about doing good research as it is about convincing people to see things your way. You work with people both easy and difficult to collaborate with to make great experiences come alive. 

Nice to Have

• MSc or PhD in Psychology, Anthropology, Sociology, HCI, Cultural Studies, or a related human behaviour field.
• Experience in high intensity consumer products, marketplaces, gaming, financial services, with some degree of experience in trust and safety is useful. 
• Experience with specialist qualitative methods: semiotics, discourse analysis, narrative research, or video ethnography.
• Proficiency with qualitative analysis tools: Dovetail, NVivo, MAXQDA, Atlas.ti, Reduct.
• Experience building or managing qualitative research panels or longitudinal participant communities.
• Published work or conference presentations in a qualitative research or HCI venue.

Why This Role at Superbet

Sports is one of the richest contexts for qualitative research: the experience is emotionally intense, socially embedded, culturally specific, and morally complex. Users have contradictory motivations. Their stated and actual behaviour diverge. The moments of joy and frustration are extreme. Understanding all of this deeply, not just what users click, but why they feel what they feel - is what separates good product decisions from great ones.

• Access to a diverse, passionate user base across 12+ markets - every cultural context brings new research challenges.
• A team that values qualitative rigour and won't ask you to reduce everything to a number.
• Senior visibility: your insights will be read by the CPO and product leadership, not just deposited in a repo.
• A Principal Quant Researcher as a genuine peer - someone to build with, argue with, and create better mixed-methods evidence with.
• Competitive compensation at Staff IC level with equity and a genuine investment in your development as a researcher.

Highlights

• Base Salary: €3,300 - €4,300 gross
• Location: Spain Remote
• Stock options
• Languages: Fluent in Russian and English 

About Fundraise Up

We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates, global payment support, and accessibility-first design.

Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact - but for the quality of the product we deliver.

A Truly Global Product

We operate in the enterprise segment, serving nonprofit organizations across North America, the United Kingdom, Australia, and Europe.

We’re building a large and complex product ecosystem that serves nonprofits, donors, and partners around the world. The platform includes a modern checkout experience and customizable widgets (each a standalone SPA), donor, organization, and partner portals, admin tools, and several internal apps.

The Team

We are a distributed team of 160+ product professionals. Our team members are mainly based across Spain, Poland, Portugal, Georgia, Armenia, Serbia, Turkey, and Cyprus. 

Despite our scale, we operate like a focused team - where every task matters and every voice is heard. We value thoughtful collaboration, strong engineering practices, and a product mindset.

About the role

Fundraise Up is building high-trust donation and fundraising experiences that help nonprofits grow their impact. We’re looking for a UX Researcher to join our Product Research Team and raise the quality, speed, and decision-making power of research across the product.

This role combines classic UX research and Product Discovery: new markets, segments, and product opportunities. You will work across both B2C and B2B contexts: donor-facing experiences (B2C) and nonprofit/org-facing workflows (B2B).

What You'll Do

• Take a research initiative from the quarterly plan and run it end-to-end: intake brief → write methodology → conduct research → analyse → synthesize → present → push actions.
• Choose the right method: interviews, usability tests, concept tests, surveys, desk research, competitive scans or others — based on uncertainty level, business goals, and timeline.
• Set up the mechanics: access to tools/data, participant scheduling and confirmations, session logistics, note-taking, recording, and documentation — no hand-holding.
• Be the cross-team “glue”: proactively collect hypotheses and context from Sales, Customer Success, Support, Marketing, Analytics, and turn them into testable research questions.
• Stay close to product analytics: monitor dashboards and reports, work with analysts to spot anomalies/drop-offs, form hypotheses, and prioritize what to validate with research.
• Produce outputs people can use immediately: key findings, decisions, trade-offs, risks, and clear recommendations, with supporting evidence (quotes, clips, metrics).
• Keep an internal pulse: regularly review existing research, past studies, competitor insights, and synthesize what’s already known before running something new.
• Be the user best friend: ensure user needs and constraints are represented in product decisions – not just opinions.

Requirements

• Proven experience running research end-to-end with high ownership.
• Strong methodological toolkit and judgment: you can pick the right method for the question, given business goals, timelines, and uncertainty, and explain trade-offs clearly.
• Experience working across both B2C and B2B products and audiences.
• Fluent English — all participants are English-speaking; you moderate and present in English.
• Can work with analytics: read dashboards, spot anomalies/drop-offs, form hypotheses, and validate them via research; PostHog/Tableau is a plus.
• Regularly collect input from Sales, CS, Support, Marketing, Analytics and turn it into testable research questions.
• High research quality bar: structured methodology, and ethical practice.
• Use recruiting platforms and handle logistics yourself: access, scheduling, confirmations, tool setup, etc.
• Use AI tools to speed up ops and synthesis (guides, notes, tagging/themes, survey drafts, summaries) while keeping human judgment and methodological rigor where it matters.
• You don’t need to be a marketer, but you should understand core terms and how they affect research and insights.
• Be the team’s source of new knowledge: run a “research radar” across internal learnings, market/competitor moves, and high-signal UX/product sources, then share regular updates so the team stays current and avoids blind spots.
• Bring exceptional empathy and care for people: our users are nonprofits and donors—people doing good in the world—so you approach participants with respect, sensitivity, and high ethical standards.

Strong plus

• NN/g certifications.
• Academic/scientific research background (graduate/PhD track).
• PostHog / Tableau (or similar analytics tools).
• Productboard (or other insights repository tools).
• Mentoring/teaching (workshops, onboarding, sharing research craft).

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 23 paid vacation days per year
• 11+ paid public holidays per year
• 5 company-paid sick leave days
• English learning courses.
• Relevant professional education.
• Gym or swimming pool.
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• Co-working.
• Remote working.

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Traditional market research is built around studies. This role is not.

At Super, we are building an AI-native research function where insight is not delivered in isolated projects, but generated continuously through systems. As a Staff Market Intelligence Researcher, your primary tool is AI—not as a shortcut, but as the infrastructure through which research happens.

You will design and operate research systems that produce high-quality consumer and market intelligence at a speed and scale that traditional agency models cannot match. Where others deliver one study in six weeks, you will deliver multiple validated insights in a fraction of the time—not by working harder, but by working differently.

This is a hands-on, high-impact individual contributor role. You will sit across Marketing Intelligence and Performance & Analytics, connecting consumer understanding directly to commercial outcomes, while building the workflows, tools, and infrastructure that make this possible.

What You’ll Be Doing

Building AI-Native Research Systems

You will move research from one-off studies to continuous intelligence systems.

• Design and run AI-moderated qualitative research at scale (e.g. interviews, concept testing, exploratory qual)
• Build repeatable workflows: survey pipelines, social listening synthesis, competitive monitoring agents
• Use LLMs to analyse large volumes of unstructured data (app reviews, transcripts, customer feedback)
• Implement validation frameworks to ensure AI outputs are reliable and decision-ready
• Optimise every workflow for speed, with most outputs delivered in days—not weeks

Delivering High-Throughput Insight

You will be the primary executor of research—not a coordinator.

• Own and triage research requests from across the marketing organisation
• Deliver insights within a two-week maximum turnaround (often faster for urgent needs)
• Translate findings into clear, actionable recommendations for marketing teams
• Run both synthetic-first validation and targeted human research where required

Owning Always-On Consumer & Brand Intelligence

You will build and maintain a live view of the consumer and brand.

• Operate a continuous brand intelligence system (pulse surveys, sentiment, social data)
• Maintain and evolve consumer segmentation frameworks
• Conduct deep qualitative research for complex or high-stakes questions
• Build and manage a structured, searchable insights library

Building Automated Competitive Intelligence

You will create a system that continuously monitors the market.

• Deploy automated agents to track competitor activity across ads, pricing, hiring, product, and media
• Synthesize signals into regular, decision-oriented competitive briefings
• Interpret what competitor activity means—not just what happened

Developing AI Research Infrastructure

You will build the foundation that enables scale.

• Own the AI research tool stack: evaluation, integration, and governance
• Create automated pipelines for intake, sampling, analysis, and delivery
• Establish best practices for responsible, rigorous AI-assisted research
• Stay ahead of emerging methodologies (synthetic research, agentic workflows, multimodal analysis)

Connecting Insight to Commercial Impact

You will bridge research with performance.

• Partner with analytics to explain performance trends through consumer understanding
• Feed insight into campaign development—not just post-campaign evaluation
• Contribute to leadership-level marketing intelligence reporting

What We Are Looking For

• 6–9 years in consumer insights or market research with strong mixed-methods expertise
• Proven experience building and running AI-augmented research workflows at scale
• Track record of operating in high-throughput, fast-paced environments
• Strong quantitative skills (survey design, sampling, analysis)
• Solid qualitative expertise (moderation, discussion design, synthesis)
• Experience with brand tracking or continuous measurement systems
• Commercial acumen—ability to connect insights to business outcomes
• Background in fast-moving digital consumer businesses (e.g. gaming, e-commerce, fintech)

Nice to Have

• Experience in gaming, sports betting, or high-LTV consumer sectors
• Familiarity with tools such as Brandwatch, Klue, Quantilop, Crayon, or similar
• Experience with AI research platforms (e.g. AI-moderated interviews, qualitative synthesis tools)
• Exposure to synthetic research methods (AI personas, simulated respondents)
• Coding experience (Python or R) for automation or analysis
• Multi-market or international research experience

Traditional market research is built around studies. This role is not.

At Super, we are building an AI-native research function where insight is not delivered in isolated projects, but generated continuously through systems. As a Staff Market Intelligence Researcher, your primary tool is AI—not as a shortcut, but as the infrastructure through which research happens.

You will design and operate research systems that produce high-quality consumer and market intelligence at a speed and scale that traditional agency models cannot match. Where others deliver one study in six weeks, you will deliver multiple validated insights in a fraction of the time—not by working harder, but by working differently.

This is a hands-on, high-impact individual contributor role. You will sit across Marketing Intelligence and Performance & Analytics, connecting consumer understanding directly to commercial outcomes, while building the workflows, tools, and infrastructure that make this possible.

What You’ll Be Doing

Building AI-Native Research Systems

You will move research from one-off studies to continuous intelligence systems.

• Design and run AI-moderated qualitative research at scale (e.g. interviews, concept testing, exploratory qual)
• Build repeatable workflows: survey pipelines, social listening synthesis, competitive monitoring agents
• Use LLMs to analyse large volumes of unstructured data (app reviews, transcripts, customer feedback)
• Implement validation frameworks to ensure AI outputs are reliable and decision-ready
• Optimise every workflow for speed, with most outputs delivered in days—not weeks

Delivering High-Throughput Insight

You will be the primary executor of research—not a coordinator.

• Own and triage research requests from across the marketing organisation
• Deliver insights within a two-week maximum turnaround (often faster for urgent needs)
• Translate findings into clear, actionable recommendations for marketing teams
• Run both synthetic-first validation and targeted human research where required

Owning Always-On Consumer & Brand Intelligence

You will build and maintain a live view of the consumer and brand.

• Operate a continuous brand intelligence system (pulse surveys, sentiment, social data)
• Maintain and evolve consumer segmentation frameworks
• Conduct deep qualitative research for complex or high-stakes questions
• Build and manage a structured, searchable insights library

Building Automated Competitive Intelligence

You will create a system that continuously monitors the market.

• Deploy automated agents to track competitor activity across ads, pricing, hiring, product, and media
• Synthesize signals into regular, decision-oriented competitive briefings
• Interpret what competitor activity means—not just what happened

Developing AI Research Infrastructure

You will build the foundation that enables scale.

• Own the AI research tool stack: evaluation, integration, and governance
• Create automated pipelines for intake, sampling, analysis, and delivery
• Establish best practices for responsible, rigorous AI-assisted research
• Stay ahead of emerging methodologies (synthetic research, agentic workflows, multimodal analysis)

Connecting Insight to Commercial Impact

You will bridge research with performance.

• Partner with analytics to explain performance trends through consumer understanding
• Feed insight into campaign development—not just post-campaign evaluation
• Contribute to leadership-level marketing intelligence reporting

What We Are Looking For

• 6–9 years in consumer insights or market research with strong mixed-methods expertise
• Proven experience building and running AI-augmented research workflows at scale
• Track record of operating in high-throughput, fast-paced environments
• Strong quantitative skills (survey design, sampling, analysis)
• Solid qualitative expertise (moderation, discussion design, synthesis)
• Experience with brand tracking or continuous measurement systems
• Commercial acumen—ability to connect insights to business outcomes
• Background in fast-moving digital consumer businesses (e.g. gaming, e-commerce, fintech)

Nice to Have

• Experience in gaming, sports betting, or high-LTV consumer sectors
• Familiarity with tools such as Brandwatch, Klue, Quantilop, Crayon, or similar
• Experience with AI research platforms (e.g. AI-moderated interviews, qualitative synthesis tools)
• Exposure to synthetic research methods (AI personas, simulated respondents)
• Coding experience (Python or R) for automation or analysis
• Multi-market or international research experience

Traditional market research is built around studies. This role is not.

At Super, we are building an AI-native research function where insight is not delivered in isolated projects, but generated continuously through systems. As a Staff Market Intelligence Researcher, your primary tool is AI—not as a shortcut, but as the infrastructure through which research happens.

You will design and operate research systems that produce high-quality consumer and market intelligence at a speed and scale that traditional agency models cannot match. Where others deliver one study in six weeks, you will deliver multiple validated insights in a fraction of the time—not by working harder, but by working differently.

This is a hands-on, high-impact individual contributor role. You will sit across Marketing Intelligence and Performance & Analytics, connecting consumer understanding directly to commercial outcomes, while building the workflows, tools, and infrastructure that make this possible.

What You’ll Be Doing

Building AI-Native Research Systems

You will move research from one-off studies to continuous intelligence systems.

• Design and run AI-moderated qualitative research at scale (e.g. interviews, concept testing, exploratory qual)
• Build repeatable workflows: survey pipelines, social listening synthesis, competitive monitoring agents
• Use LLMs to analyse large volumes of unstructured data (app reviews, transcripts, customer feedback)
• Implement validation frameworks to ensure AI outputs are reliable and decision-ready
• Optimise every workflow for speed, with most outputs delivered in days—not weeks

Delivering High-Throughput Insight

You will be the primary executor of research—not a coordinator.

• Own and triage research requests from across the marketing organisation
• Deliver insights within a two-week maximum turnaround (often faster for urgent needs)
• Translate findings into clear, actionable recommendations for marketing teams
• Run both synthetic-first validation and targeted human research where required

Owning Always-On Consumer & Brand Intelligence

You will build and maintain a live view of the consumer and brand.

• Operate a continuous brand intelligence system (pulse surveys, sentiment, social data)
• Maintain and evolve consumer segmentation frameworks
• Conduct deep qualitative research for complex or high-stakes questions
• Build and manage a structured, searchable insights library

Building Automated Competitive Intelligence

You will create a system that continuously monitors the market.

• Deploy automated agents to track competitor activity across ads, pricing, hiring, product, and media
• Synthesize signals into regular, decision-oriented competitive briefings
• Interpret what competitor activity means—not just what happened

Developing AI Research Infrastructure

You will build the foundation that enables scale.

• Own the AI research tool stack: evaluation, integration, and governance
• Create automated pipelines for intake, sampling, analysis, and delivery
• Establish best practices for responsible, rigorous AI-assisted research
• Stay ahead of emerging methodologies (synthetic research, agentic workflows, multimodal analysis)

Connecting Insight to Commercial Impact

You will bridge research with performance.

• Partner with analytics to explain performance trends through consumer understanding
• Feed insight into campaign development—not just post-campaign evaluation
• Contribute to leadership-level marketing intelligence reporting

What We Are Looking For

• 6–9 years in consumer insights or market research with strong mixed-methods expertise
• Proven experience building and running AI-augmented research workflows at scale
• Track record of operating in high-throughput, fast-paced environments
• Strong quantitative skills (survey design, sampling, analysis)
• Solid qualitative expertise (moderation, discussion design, synthesis)
• Experience with brand tracking or continuous measurement systems
• Commercial acumen—ability to connect insights to business outcomes
• Background in fast-moving digital consumer businesses (e.g. gaming, e-commerce, fintech)

Nice to Have

• Experience in gaming, sports betting, or high-LTV consumer sectors
• Familiarity with tools such as Brandwatch, Klue, Quantilop, Crayon, or similar
• Experience with AI research platforms (e.g. AI-moderated interviews, qualitative synthesis tools)
• Exposure to synthetic research methods (AI personas, simulated respondents)
• Coding experience (Python or R) for automation or analysis
• Multi-market or international research experience

An overview of this role

GitLab is looking for a Product Design Manager to join the Plan & Analytics stage. As a design leader, you own the delivery of UX commitments, are always looking to improve productivity, and are responsible for the user experience in the product. While you are credible as a designer and know the details of what product designers work on, your time is spent hiring a world-class team and putting them in the best position to succeed.

This is an incredibly exciting time to join the Plan & Analytics stages - Working in GitLab's Plan space sits at the most human and strategic layer of the software development lifecycle — where ideas, priorities, and intentions are formed — making it the perfect frontier to explore how AI can augment not just execution, but thinking itself. As AI accelerates the speed at which code is written and shipped, the Plan space becomes even more critical, because the bottleneck is rapidly shifting from "how fast can we build?" to "how clearly can we define what to build and why?" This creates a rare opportunity to reimagine how teams collaborate, how requirements evolve, and how AI can transform a traditionally manual, document-heavy process into a dynamic, intelligent system that connects strategy directly to delivery.

You'll be working closely with the Product Management and Engineering teams to execute on the product roadmap and priorities.

Some examples of our projects: 

• Work Items
• Saved Views
• Software Factory

What you’ll do  

• Proactively identify large, strategic UX opportunities that span both inside your areas and across the product. Work with other product design managers, staff, and principal product designers to drive cross-product initiatives through awareness and prioritization.
• Identify strategic user research initiatives that span multiple stage groups (and possibly the entire product), and work with other product design/research managers to organize research efforts.
• Be a frequent and active participant in milestones by reviewing UX deliverables (such as research and designs) that your team creates, and provide feedback to ensure high-quality output.
• Communicate the value of UX to cross-functional GitLab team members and work with them to leverage the product development flow. 
• Help the product teams of areas you support to prioritize UX initiatives including Deferred UX, triage and resolution of UX bugs, and overall usability improvements to the product. Lead UX Scorecard initiatives in order to consistently measure the experience of your product areas and show improvements over time.
• Contribute to product direction conversations, with emphasis on leading the experience vision for your product areas.
• Hire, grow and retain a world-class team of Designers.

What you’ll bring 

• Experience managing a group of designers remotely, who work on complex products.
• Deep experience building AI experience for the software development lifecycle.
• Deep experience designing for large-scale enterprise platforms.
• Experience defining/executing on the high-level strategy (the why) and creating design deliverables (the how) based on research.
• Experience driving organizational change with cross-functional stakeholders, including Product Management and Engineering.
• Solid visual awareness with understanding of basic design principles and accessibility.
• You share our values, and work in accordance with those values.
• You possess leadership qualities needed to thrive at Gitlab.
• Ability to use GitLab.

About the team

You will work closely with three designers. You will collaborate with the Group Product Manager, Engineering Director and UX Researcher to improve team communication and maintain excitement about the opportunities ahead. You can learn more about what our teams are working on by visiting our direction page:

• Plan

About the role

We're looking for a Senior UX Researcher who brings rigour and curiosity to both product and marketing research. Someone who's as comfortable running foundational product studies as they are digging into brand perception, buyer mindsets, or how a marketing site actually works for the people using it.

This is strategic, high-visibility work — you'll partner with Product Design, Product Management, Brand, and Marketing to shape what we build and how we tell the world about it.

What makes this role unique:

• Work across both brand and product research, with real influence on each
• Research enterprise developer tools and DevOps workflows — including AI-powered features built for developers
• Fast-paced environment where research directly influences design and business decisions
• Be part of a team of talented, experienced researchers who genuinely invest in each other's growth

What you'll do

• Lead foundational, problem validation, and strategic research projects across your assigned product areas and beyond
• Drive both brand and product research — including buyer persona development, brand perception studies, and digital experience research — that directly informs positioning and messaging
• Be the expert on the users within your area of coverage: their behaviours, pain points, workflows, and goals
• Make connections across research initiatives, surfacing macro insights that no single study could reveal on its own
• Build trusted relationships with Product Design, Product Management, Brand, and Marketing counterparts, guiding them to the right research approach
• Advocate for and socialise actionable insights in a clear and compelling way that increases empathy across the organisation
• Independently drive research prioritisation across stage groups, balancing impact, product direction, and company objectives
• Mentor other researchers and actively shape how the Experience Research team works, through process iteration, documentation, and peer reviews

What you'll bring

• Empathetic, curious and open-minded
• Deep mixed-methods research experience across qualitative and quantitative methods
• A track record in both product research and marketing or brand research
• The ability to guide stakeholders — including senior ones — toward the right approach, even when they arrive with a firm opinion
• Strong instincts for prioritisation across multiple stakeholder groups in a fast-moving environment
• Clear, compelling communication that makes findings land with product, brand, and marketing audiences
• Experience working in a highly iterative, fast-paced environment, with the ability to pivot with sudden changes in direction
• Demonstrated ability to work effectively in a fully remote, globally distributed team — with strong async communication habits
• Self-motivated and self-managing, with strong organisational skills
• Ability to ramp up to a highly technical domain quickly
• Share our values, and work in accordance with those values
• Able to conduct research in a fully remote setting and use GitLab as part of your daily workflow
• Experience working on AI products, particularly for enterprise dev tooling, is a plus
• Experience working on enterprise and/or developer tooling products is a plus

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior ML Researcher to develop the core methods that make Spectrum possible – novel approaches to temporal ontology extraction, contradiction detection, and semantic alignment across heterogeneous software artifacts. You will help define and execute the research agenda, while also collaborating with JetBrains Research and external academic advisors.

Your responsibilities will include:

• Developing methods for LLM-based ontology construction from code, documentation, and issue trackers, including contradiction detection and reasoning over the resulting knowledge graph.
• Creating datasets, metrics, and benchmarks that drive measurable improvements across the system.
• Prototyping and validating research ideas, then collaborating with ML and software engineers to bring them to production.
• Collaborating with JetBrains Research and external academic advisors to shape our research agenda.
• Publishing research findings at top venues and representing Spectrum in the research community.

We expect you to have:

• A PhD (or equivalent research experience) in NLP, knowledge graphs, ontology learning, information extraction, or a closely related field.
• A strong publication record in at least one of the following areas: knowledge graph construction, ontology learning, information extraction, or NLP.
• Experience applying LLMs to structured knowledge extraction tasks.
• Experience designing and running rigorous experiments, including hypothesis formulation, ablation studies, and statistical evaluation.
• Strong Python and PyTorch skills, with the ability to implement research ideas from scratch.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontology engineering, semantic web technologies (OWL, RDF, SPARQL), or ontology alignment.
• A background in code analysis, developer tools, or software engineering research.
• Experience with knowledge graph embedding methods or graph neural networks.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• Actively contributed to relevant open-source projects.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• Full support for publishing ML research and attending industry conferences.
• Collaboration with JetBrains Research and external academic advisors in the knowledge graph and ontology learning community.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• A rare applied research role where your methods ship in a real product used by software teams.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

About the role-

We’re looking for an Engineering Manager to join our Models team, an experimental driven tribe working at the intersection of engineering, data science, and product to deliver performant, accurate, and scalable systems powering the pricing logic behind our sportsbook.

You’ll work with quant models, simulations, and pricing systems that are critical to how Superbet engages customers. This role combines technical leadership, people development, and delivery management to ensure engineering quality and team clarity across both model integration and operational ownership.

You’ll also contribute to maturing our engineering practices; including system reliability, observability, testing, CI/CD, and documentation, driving best practices within the team as we scale the platform and grow the team.

We’re looking for someone who has:

• Proven experience in engineering leadership, across both people and delivery
• Strong technical background-ideally in backend systems, distributed architecture, or real-time data platforms
• Experience in hiring and developing engineering teams, including mentoring, 1:1s, and career development
• Demonstrated ability to build team culture and engineering discipline
• Comfort balancing business delivery and engineering health (tech debt, infra, documentation)
• Strong exposure to on-call responsibilities and improving production reliability
• History of working in cross-functional teams and aligning with product and engineering stakeholders
• Deep understanding of the software development lifecycle
• Effective at resolving complex engineering and communication issues
• Great time management, organisational, and multitasking skills

Bonus points for:

• Experience in iGaming, especially within Sportsbook or Trading domains
• Familiarity with quantitative modelling workflows and their engineering lifecycle
• Experience in simulation platforms, ML pipelines, or pricing systems
• Ability to lead teams through experimental or uncertain development environments
• Hands-on experience driving or improving Agile development practices

What you’ll be doing:

• Lead a team of engineers delivering and supporting pricing models and simulations at scale
• Partner with analysts, PMs, and engineering peers to improve the accuracy, testability, and stability of pricing systems
• Strengthen relationships with Product, Quant, and Data Science to ensure alignment and clarity in delivery
• Promote a culture of ownership, clarity, and best practice in engineering
• Ensure balance between product delivery and tech initiatives-creating room for improvements in infrastructure, standards, and long-term scalability
• Support individual engineers through structured feedback, career development, and regular check-ins
• Drive hiring and contribute to a strong culture of engineering excellence and documentation across the mission

We're building an AI copilot for web testing automation. It enables manual and automation QA engineers to turn their manual testing flows into production-ready automated E2E testing scripts, saving hours of manual work and coding. We are a small team with zero bureaucracy, focusing on real users. We optimize for shipping value - not hype.

About the role:

You'll own the top of the funnel: outbound, qualification, and getting leads to sit down for a conversation. Demos, onboarding, and retention are staying with the founder for now.

Phase one: Get individual Automation QAs to try the product, aiming for fast adoption and no procurement. Once we hit 20+ weekly users, we’ll move on to phase two, where we’ll shift the focus to B2B – qualified meetings with QA Leads and Engineering Managers.

Your focus in the first three months:

• Build targeted lists: Automation QAs at companies with web products and Playwright, Cypress, or Selenium in their stack.
• Run outbound sequences (LinkedIn is the baseline, but you decide the channels). A/B test weekly.
• Design qualification gates (forms and scoring) to filter leads before the founder calls.
• Reach 20+ weekly active users after month one – ICP-qualified and giving direct feedback to engineering.
• Document what works into a repeatable playbook.

Growth path:

This role expands as your strategies deliver results. Once the user pipeline works, you can take over demos and run B2B sales end to end. From there, the natural next step is Growth Lead (funnel optimization and scaling the playbook) or Account Executive (owning deal execution).

Why to join:

• You'll be building a strategy that scales the product, not filling a quota. What you create from scratch becomes the foundation.
• Your outreach turns into users who talk directly to engineering, and their feedback ships as features within days.
• AI for developer tools is a market with real pull, and QA automation is one of its sharpest pain points.
• We’re backed by JetBrains – financially secure with no reliance on external VC funding.

Who we're looking for:

You should have a high level of agency and be quant-minded – you live in funnel metrics, run experiments, and are comfortable saying "no" to leads that are a bad fit. 

The ideal candidate will:

• Have done 0-to-1 outbound for an early-stage devtool, QA tool, infrastructure product, or similar.
• Have proven cold outbound results, instead of being dependent on warm inbound.
• Be able to talk credibly about flaky tests, CI pain, and Playwright vs. Cypress. You don't need to be an engineer, but you do need domain empathy.
• Possess strong written communication skills, with the ability to craft short, sharp messages that get replies.

Nice to have:

• A QA or SDET background – you've felt the pain yourself before moving to sales or BD.
• Exposure to security/compliance objections – enough to pre-empt and route.
• Content skills – your LinkedIn posts get engagement, not just your DMs.
• Experience as one of the first 10 employees at a startup.

#LI-REMOTE 
#LI-KT1

About the Role

Superbet is building the future of gaming experiences, and we need a visionary lead to architect our AI-first UX Research Operations function from the ground up. This is a rare opportunity to define how AI transforms research at scale - moving from traditional qual/quant methods to intelligent, automated insight generation that keeps pace with our global expansion. 

You'll be the bridge between cutting-edge AI capabilities and human-centered research excellence, building systems that allow our product teams to make confident, data-informed decisions 10x faster than traditional research allows. 

This is not a traditional ResearchOps role. We're looking for someone who sees AI as the primary research infrastructure, not just a productivity tool. 

You bring methodological mastery, creative curiosity, and the kind of presence that makes participants forget they're being observed and leaders believe you shape company wide narratives. You also bring a future positive mindset: you are actively integrating AI tools into your workflow to do more, faster, without sacrificing the depth that makes qual irreplaceable. You know when AI is helpful and when it is not and can help junior researchers make decisions around when to use them. 

What You Will Build

Year 1: Foundation

• AI Research Infrastructure: Design and implement an AI-native research stack that automates insight synthesis, pattern detection, and continuous discovery 
• Intelligent Repository: Build a living research knowledge base where AI surfaces relevant insights the moment teams need them—no searching through Notion or Dovetail 
• Automated Research Workflows: Deploy AI agents for interview transcription, analysis, synthesis, competitive intelligence, and sentiment monitoring across 12+ markets 
• Research Democratization: Enable product managers, designers, and engineers to self-serve 80% of research questions through AI-assisted tools 

Year 2: Scale 

• Continuous User Understanding: Establish always-on research systems (AI-powered surveys, behavioral analytics, community listening) that generate insights without manual studies Predictive Research: Build models that anticipate user needs, friction points, and opportunities before traditional research would surface them 
• Cross-Market Intelligence: Create AI systems that synthesize insights across Superbet's global markets, detecting regional patterns and universal truths 
• Research Quality Assurance: Implement AI-assisted validation frameworks to ensure insights are reliable, unbiased, and actionable

Year 3: Always On Insights 

• AI predicts user friction points before traditional research surfaces them 
• Cross-market insight synthesis happens automatically 
• Research velocity 10x faster than traditional methods 
• Industry-leading case study: "How Superbet built AI-first research" 

What Success Looks Like 

6 Months:

• - AI research stack operational across 3+ product teams 
• - 50% reduction in time-to-insight for common research questions 
• - Research knowledge base with 100+ synthesized insights, AI-searchable 

12 Months: - Product teams self-serve 70%+ of research needs through AI tools - Continuous user understanding systems running across all markets - Research influences 90%+ of major product decisions 

What We Are Looking For

Basic Experience

• Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• Experience working cross functionally with tech and non-tech teams
• Experience defining program requirements and using data and metrics to determine improvements
• Experience in program or project management
• Experience implementing repeatable processes and driving automation or standardization
• Experience defining and executing program requirements within strict timelines

Essential Experience

ResearchOps Excellence (Critical) - Built research operations from 0→1 at a high-growth company - Designed research repositories, tooling stacks, and democratization programs- Managed research panels, participant recruitment, and compliance frameworks- Scaled research to support 50+ stakeholders across multiple product teams AI & Research Intersection (Critical) 

• - 5+ years in UX Research, with 2+ years actively using AI in research workflows
• - Shipped AI-powered research tools, processes, or platforms (not just "used ChatGPT") 
• - Deep understanding of LLMs, RAG systems, prompt engineering for research applications 
• - Experience evaluating AI research tools and building AI-augmented research practices 
• Technical Acumen (Critical) 
• - Comfortable reading code, writing SQL, or working with APIs 
• - Built custom AI workflows (GPT API, Claude API, Zapier, Make) 

Industry Context (Preferred) - Experience in regulated industries (gambling, fintech, healthcare)- Multi-market or international research experience - Background in high-velocity product environments (weekly releases) 

Skills & Mindset

• World-class operator: You have a gift for going across the organization to find the most optimal ways of work - time, money, resource wise.
• AI-enhanced, not AI-dependent: You use AI to go faster and deeper, but your analytical judgement is irreplaceable and you know it. You apply AI tools critically, not uncritically.
• Meticulous planner: You are an expert in Operations and constantly keep improving the team’s delivery model.  
• Org Mover: Your research is not theory alone, you know how to make things tangible, bite sized and move people and work forward. 
• Embrace difficult conversations - Driving research impact is as much about doing good research as it is about convincing people to see things your way. You work with people both easy and difficult to collaborate with to make great experiences come alive. 
• Frugal: You continuously improve our spending habits and drive financial efficiency for the org. 

Nice to Have

• Experience in high intensity consumer products, marketplaces, gaming, financial services, with some degree of experience in trust and safety is useful. 
• Experience in launching new programs, markets and changing large scale work processes in short turn around.
• Experience in some European languages. 

Why This Role at Superbet

Sports is one of the richest contexts for qualitative research: the experience is emotionally intense, socially embedded, culturally specific, and morally complex. Users have contradictory motivations. Their stated and actual behaviour diverge. The moments of joy and frustration are extreme. Understanding all of this deeply, not just what users click, but why they feel what they feel - is what separates good product decisions from great ones.

• Access to a diverse, passionate user base across 12+ markets - every cultural context brings new research challenges.
• A team that values qualitative rigour and won't ask you to reduce everything to a number.
• Senior visibility: your insights will be read by the CPO and product leadership, not just deposited in a repo.
• A Principal Quant Researcher as a genuine peer - someone to build with, argue with, and create better mixed-methods evidence with.
• Competitive compensation at Staff IC level with equity and a genuine investment in your development as a researcher.

About the Role

Superbet is building the future of gaming experiences, and we need a visionary lead to architect our AI-first UX Research Operations function from the ground up. This is a rare opportunity to define how AI transforms research at scale - moving from traditional qual/quant methods to intelligent, automated insight generation that keeps pace with our global expansion. 

You'll be the bridge between cutting-edge AI capabilities and human-centered research excellence, building systems that allow our product teams to make confident, data-informed decisions 10x faster than traditional research allows. 

This is not a traditional ResearchOps role. We're looking for someone who sees AI as the primary research infrastructure, not just a productivity tool. 

You bring methodological mastery, creative curiosity, and the kind of presence that makes participants forget they're being observed and leaders believe you shape company wide narratives. You also bring a future positive mindset: you are actively integrating AI tools into your workflow to do more, faster, without sacrificing the depth that makes qual irreplaceable. You know when AI is helpful and when it is not and can help junior researchers make decisions around when to use them. 

What You Will Build

Year 1: Foundation

• AI Research Infrastructure: Design and implement an AI-native research stack that automates insight synthesis, pattern detection, and continuous discovery 
• Intelligent Repository: Build a living research knowledge base where AI surfaces relevant insights the moment teams need them—no searching through Notion or Dovetail 
• Automated Research Workflows: Deploy AI agents for interview transcription, analysis, synthesis, competitive intelligence, and sentiment monitoring across 12+ markets 
• Research Democratization: Enable product managers, designers, and engineers to self-serve 80% of research questions through AI-assisted tools 

Year 2: Scale 

• Continuous User Understanding: Establish always-on research systems (AI-powered surveys, behavioral analytics, community listening) that generate insights without manual studies Predictive Research: Build models that anticipate user needs, friction points, and opportunities before traditional research would surface them 
• Cross-Market Intelligence: Create AI systems that synthesize insights across Superbet's global markets, detecting regional patterns and universal truths 
• Research Quality Assurance: Implement AI-assisted validation frameworks to ensure insights are reliable, unbiased, and actionable

Year 3: Always On Insights 

• AI predicts user friction points before traditional research surfaces them 
• Cross-market insight synthesis happens automatically 
• Research velocity 10x faster than traditional methods 
• Industry-leading case study: "How Superbet built AI-first research" 

What Success Looks Like 

6 Months:

• - AI research stack operational across 3+ product teams 
• - 50% reduction in time-to-insight for common research questions 
• - Research knowledge base with 100+ synthesized insights, AI-searchable 

12 Months: - Product teams self-serve 70%+ of research needs through AI tools - Continuous user understanding systems running across all markets - Research influences 90%+ of major product decisions 

What We Are Looking For

Basic Experience

• Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• Experience working cross functionally with tech and non-tech teams
• Experience defining program requirements and using data and metrics to determine improvements
• Experience in program or project management
• Experience implementing repeatable processes and driving automation or standardization
• Experience defining and executing program requirements within strict timelines

Essential Experience

ResearchOps Excellence (Critical) - Built research operations from 0→1 at a high-growth company - Designed research repositories, tooling stacks, and democratization programs- Managed research panels, participant recruitment, and compliance frameworks- Scaled research to support 50+ stakeholders across multiple product teams AI & Research Intersection (Critical) 

• - 5+ years in UX Research, with 2+ years actively using AI in research workflows
• - Shipped AI-powered research tools, processes, or platforms (not just "used ChatGPT") 
• - Deep understanding of LLMs, RAG systems, prompt engineering for research applications 
• - Experience evaluating AI research tools and building AI-augmented research practices 
• Technical Acumen (Critical) 
• - Comfortable reading code, writing SQL, or working with APIs 
• - Built custom AI workflows (GPT API, Claude API, Zapier, Make) 

Industry Context (Preferred) - Experience in regulated industries (gambling, fintech, healthcare)- Multi-market or international research experience - Background in high-velocity product environments (weekly releases) 

Skills & Mindset

• World-class operator: You have a gift for going across the organization to find the most optimal ways of work - time, money, resource wise.
• AI-enhanced, not AI-dependent: You use AI to go faster and deeper, but your analytical judgement is irreplaceable and you know it. You apply AI tools critically, not uncritically.
• Meticulous planner: You are an expert in Operations and constantly keep improving the team’s delivery model.  
• Org Mover: Your research is not theory alone, you know how to make things tangible, bite sized and move people and work forward. 
• Embrace difficult conversations - Driving research impact is as much about doing good research as it is about convincing people to see things your way. You work with people both easy and difficult to collaborate with to make great experiences come alive. 
• Frugal: You continuously improve our spending habits and drive financial efficiency for the org. 

Nice to Have

• Experience in high intensity consumer products, marketplaces, gaming, financial services, with some degree of experience in trust and safety is useful. 
• Experience in launching new programs, markets and changing large scale work processes in short turn around.
• Experience in some European languages. 

Why This Role at Superbet

Sports is one of the richest contexts for qualitative research: the experience is emotionally intense, socially embedded, culturally specific, and morally complex. Users have contradictory motivations. Their stated and actual behaviour diverge. The moments of joy and frustration are extreme. Understanding all of this deeply, not just what users click, but why they feel what they feel - is what separates good product decisions from great ones.

• Access to a diverse, passionate user base across 12+ markets - every cultural context brings new research challenges.
• A team that values qualitative rigour and won't ask you to reduce everything to a number.
• Senior visibility: your insights will be read by the CPO and product leadership, not just deposited in a repo.
• A Principal Quant Researcher as a genuine peer - someone to build with, argue with, and create better mixed-methods evidence with.
• Competitive compensation at Staff IC level with equity and a genuine investment in your development as a researcher.

About the Role

Superbet is building the future of gaming experiences, and we need a visionary lead to architect our AI-first UX Research Operations function from the ground up. This is a rare opportunity to define how AI transforms research at scale - moving from traditional qual/quant methods to intelligent, automated insight generation that keeps pace with our global expansion. 

You'll be the bridge between cutting-edge AI capabilities and human-centered research excellence, building systems that allow our product teams to make confident, data-informed decisions 10x faster than traditional research allows. 

This is not a traditional ResearchOps role. We're looking for someone who sees AI as the primary research infrastructure, not just a productivity tool. 

You bring methodological mastery, creative curiosity, and the kind of presence that makes participants forget they're being observed and leaders believe you shape company wide narratives. You also bring a future positive mindset: you are actively integrating AI tools into your workflow to do more, faster, without sacrificing the depth that makes qual irreplaceable. You know when AI is helpful and when it is not and can help junior researchers make decisions around when to use them. 

What You Will Build

Year 1: Foundation

• AI Research Infrastructure: Design and implement an AI-native research stack that automates insight synthesis, pattern detection, and continuous discovery 
• Intelligent Repository: Build a living research knowledge base where AI surfaces relevant insights the moment teams need them—no searching through Notion or Dovetail 
• Automated Research Workflows: Deploy AI agents for interview transcription, analysis, synthesis, competitive intelligence, and sentiment monitoring across 12+ markets 
• Research Democratization: Enable product managers, designers, and engineers to self-serve 80% of research questions through AI-assisted tools 

Year 2: Scale 

• Continuous User Understanding: Establish always-on research systems (AI-powered surveys, behavioral analytics, community listening) that generate insights without manual studies Predictive Research: Build models that anticipate user needs, friction points, and opportunities before traditional research would surface them 
• Cross-Market Intelligence: Create AI systems that synthesize insights across Superbet's global markets, detecting regional patterns and universal truths 
• Research Quality Assurance: Implement AI-assisted validation frameworks to ensure insights are reliable, unbiased, and actionable

Year 3: Always On Insights 

• AI predicts user friction points before traditional research surfaces them 
• Cross-market insight synthesis happens automatically 
• Research velocity 10x faster than traditional methods 
• Industry-leading case study: "How Superbet built AI-first research" 

What Success Looks Like 

6 Months:

• - AI research stack operational across 3+ product teams 
• - 50% reduction in time-to-insight for common research questions 
• - Research knowledge base with 100+ synthesized insights, AI-searchable 

12 Months: - Product teams self-serve 70%+ of research needs through AI tools - Continuous user understanding systems running across all markets - Research influences 90%+ of major product decisions 

What We Are Looking For

Basic Experience

• Knowledge of Excel (Pivot Tables, VLookUps) at an advanced level and SQL
• Experience working cross functionally with tech and non-tech teams
• Experience defining program requirements and using data and metrics to determine improvements
• Experience in program or project management
• Experience implementing repeatable processes and driving automation or standardization
• Experience defining and executing program requirements within strict timelines

Essential Experience

ResearchOps Excellence (Critical) - Built research operations from 0→1 at a high-growth company - Designed research repositories, tooling stacks, and democratization programs- Managed research panels, participant recruitment, and compliance frameworks- Scaled research to support 50+ stakeholders across multiple product teams AI & Research Intersection (Critical) 

• - 5+ years in UX Research, with 2+ years actively using AI in research workflows
• - Shipped AI-powered research tools, processes, or platforms (not just "used ChatGPT") 
• - Deep understanding of LLMs, RAG systems, prompt engineering for research applications 
• - Experience evaluating AI research tools and building AI-augmented research practices 
• Technical Acumen (Critical) 
• - Comfortable reading code, writing SQL, or working with APIs 
• - Built custom AI workflows (GPT API, Claude API, Zapier, Make) 

Industry Context (Preferred) - Experience in regulated industries (gambling, fintech, healthcare)- Multi-market or international research experience - Background in high-velocity product environments (weekly releases) 

Skills & Mindset

• World-class operator: You have a gift for going across the organization to find the most optimal ways of work - time, money, resource wise.
• AI-enhanced, not AI-dependent: You use AI to go faster and deeper, but your analytical judgement is irreplaceable and you know it. You apply AI tools critically, not uncritically.
• Meticulous planner: You are an expert in Operations and constantly keep improving the team’s delivery model.  
• Org Mover: Your research is not theory alone, you know how to make things tangible, bite sized and move people and work forward. 
• Embrace difficult conversations - Driving research impact is as much about doing good research as it is about convincing people to see things your way. You work with people both easy and difficult to collaborate with to make great experiences come alive. 
• Frugal: You continuously improve our spending habits and drive financial efficiency for the org. 

Nice to Have

• Experience in high intensity consumer products, marketplaces, gaming, financial services, with some degree of experience in trust and safety is useful. 
• Experience in launching new programs, markets and changing large scale work processes in short turn around.
• Experience in some European languages. 

Why This Role at Superbet

Sports is one of the richest contexts for qualitative research: the experience is emotionally intense, socially embedded, culturally specific, and morally complex. Users have contradictory motivations. Their stated and actual behaviour diverge. The moments of joy and frustration are extreme. Understanding all of this deeply, not just what users click, but why they feel what they feel - is what separates good product decisions from great ones.

• Access to a diverse, passionate user base across 12+ markets - every cultural context brings new research challenges.
• A team that values qualitative rigour and won't ask you to reduce everything to a number.
• Senior visibility: your insights will be read by the CPO and product leadership, not just deposited in a repo.
• A Principal Quant Researcher as a genuine peer - someone to build with, argue with, and create better mixed-methods evidence with.
• Competitive compensation at Staff IC level with equity and a genuine investment in your development as a researcher.

Super Technologies is scaling, and we’re expanding our P&T Talent Acquisition team.
We are looking for an experienced Tech Sourcer with a passion for discovering and engaging high-impact Product & Technology talent across global markets.

What you’ll be doing? Responsibilities.


• Proactively source and identify top talent for Product & Technology roles (Engineering, Product, Data, QA, Design, Platform, Security, PMO, etc.).
• Build long-term talent pipelines for critical skill areas and future hiring needs, using tools such as LinkedIn Recruiter, GitHub, job boards and talent communities.
• Conduct initial outreach and candidate screenings to evaluate technical alignment and motivation while serving as a primary ambassador for Super Technologies’ culture and values.
• Partner closely with Talent Acquisition Partners and hiring managers to understand role requirements and refine sourcing strategies.
• Track and manage candidates via our ATS (Greenhouse) ensuring accurate data, progress tracking and pipeline health.
• Deliver high-quality shortlists and insights to TA Partners and hiring teams, enriching market understanding and decision-making.
• Experiment with creative sourcing tactics: referrals, social channels and niche platforms to access diverse and hard-to-find candidate pools.
• Collaborate across markets and teams to share sourcing best practices, tools, and market intelligence.

You’ll thrive in this role if you:


• Bring 2-3 years of experience as a Sourcer or Talent Researcher, ideally within Product & Tech positions.
• Are confident navigating LinkedIn Recruiter, and advanced sourcing.
• Understand common product and engineering profiles and can translate job requirements into sourcing priorities.
• Enjoy building pipelines proactively rather than reacting to open roles.
• Have experience qualifying candidates and assessing technical basics (you don’t need to code but you should speak the language!).
• Communicate clearly, build rapport quickly and create excitement around Super Technologies.
• Work effectively in a fast-moving, international environment with shifting priorities and volume cycles.
• Organize your work independently, track pipelines clearly and deliver consistently.
• Have experience with ATS tools and value clean data and process discipline.
• Passionate to learn about new technologies, markets and sourcing channels as the talent landscape evolves.

Super Technologies is scaling, and we’re expanding our P&T Talent Acquisition team.
We are looking for an experienced Tech Sourcer with a passion for discovering and engaging high-impact Product & Technology talent across global markets.

What you’ll be doing? Responsibilities.


• Proactively source and identify top talent for Product & Technology roles (Engineering, Product, Data, QA, Design, Platform, Security, PMO, etc.).
• Build long-term talent pipelines for critical skill areas and future hiring needs, using tools such as LinkedIn Recruiter, GitHub, job boards and talent communities.
• Conduct initial outreach and candidate screenings to evaluate technical alignment and motivation while serving as a primary ambassador for Super Technologies’ culture and values.
• Partner closely with Talent Acquisition Partners and hiring managers to understand role requirements and refine sourcing strategies.
• Track and manage candidates via our ATS (Greenhouse) ensuring accurate data, progress tracking and pipeline health.
• Deliver high-quality shortlists and insights to TA Partners and hiring teams, enriching market understanding and decision-making.
• Experiment with creative sourcing tactics: referrals, social channels and niche platforms to access diverse and hard-to-find candidate pools.
• Collaborate across markets and teams to share sourcing best practices, tools, and market intelligence.

You’ll thrive in this role if you:


• Bring 2-3 years of experience as a Sourcer or Talent Researcher, ideally within Product & Tech positions.
• Are confident navigating LinkedIn Recruiter, and advanced sourcing.
• Understand common product and engineering profiles and can translate job requirements into sourcing priorities.
• Enjoy building pipelines proactively rather than reacting to open roles.
• Have experience qualifying candidates and assessing technical basics (you don’t need to code but you should speak the language!).
• Communicate clearly, build rapport quickly and create excitement around Super Technologies.
• Work effectively in a fast-moving, international environment with shifting priorities and volume cycles.
• Organize your work independently, track pipelines clearly and deliver consistently.
• Have experience with ATS tools and value clean data and process discipline.
• Passionate to learn about new technologies, markets and sourcing channels as the talent landscape evolves.

Super Technologies is scaling, and we’re expanding our P&T Talent Acquisition team.
We are looking for an experienced Tech Sourcer with a passion for discovering and engaging high-impact Product & Technology talent across global markets.

What you’ll be doing? Responsibilities.


• Proactively source and identify top talent for Product & Technology roles (Engineering, Product, Data, QA, Design, Platform, Security, PMO, etc.).
• Build long-term talent pipelines for critical skill areas and future hiring needs, using tools such as LinkedIn Recruiter, GitHub, job boards and talent communities.
• Conduct initial outreach and candidate screenings to evaluate technical alignment and motivation while serving as a primary ambassador for Super Technologies’ culture and values.
• Partner closely with Talent Acquisition Partners and hiring managers to understand role requirements and refine sourcing strategies.
• Track and manage candidates via our ATS (Greenhouse) ensuring accurate data, progress tracking and pipeline health.
• Deliver high-quality shortlists and insights to TA Partners and hiring teams, enriching market understanding and decision-making.
• Experiment with creative sourcing tactics: referrals, social channels and niche platforms to access diverse and hard-to-find candidate pools.
• Collaborate across markets and teams to share sourcing best practices, tools, and market intelligence.

You’ll thrive in this role if you:


• Bring 2-3 years of experience as a Sourcer or Talent Researcher, ideally within Product & Tech positions.
• Are confident navigating LinkedIn Recruiter, and advanced sourcing.
• Understand common product and engineering profiles and can translate job requirements into sourcing priorities.
• Enjoy building pipelines proactively rather than reacting to open roles.
• Have experience qualifying candidates and assessing technical basics (you don’t need to code but you should speak the language!).
• Communicate clearly, build rapport quickly and create excitement around Super Technologies.
• Work effectively in a fast-moving, international environment with shifting priorities and volume cycles.
• Organize your work independently, track pipelines clearly and deliver consistently.
• Have experience with ATS tools and value clean data and process discipline.
• Passionate to learn about new technologies, markets and sourcing channels as the talent landscape evolves.