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.

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.

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

At Superbet, data isn’t a support function, it’s at the heart of every major decision we make. As a Data Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behavior, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

At Super Technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Data Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behavior, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Super Technologies to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Super Technologies moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical and ML methods and bringing them to life in dashboards (we use Tableau). It would be also great if you have experience/basic knowledge of python or R.
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engineering, Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 4+ years of relevant experience.

The Role

At Super, data isn’t a support function. It’s at the heart of every major decision we make.

As a Senior Product Data Scientist, you’ll operate at the intersection of product and strategy, owning decision-making, problem framing, and hypothesis generation. Your work won’t sit in slide decks. It will directly shape how millions of customers engage with our products.

This is a role for a very special kind of data scientist: someone who loves hard problems, thrives in ambiguity, and gets energised by moving from messy questions to clear decisions that drive strategy.

You’ll be expected to not just report what happened, but to uncover why through causal inference, anticipate what’s next, and produce decision memos that influence what we should do about it.

You’ll work in close partnership with Analytics Engineers, who build and maintain production data products. Your role is to define what needs to be measured and why, while AE ensures scalable, trustworthy data infrastructure.

What You’ll Do

Be the Decision Engine

• Run deep-dive analyses into customer behaviour, product usage, and commercial performance.
• Go beyond surface-level metrics to uncover causal drivers behind phenomena using rigorous statistical methods.
• Distinguish correlation from cause-and-effect.

Shape Strategy with Data

• Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions.
• Design and analyse experiments, including A/B tests and quasi-experiments.
• Deliver decision memos that change the course of decisions, with quantified impact ranges and clear “so what” guidance for Directors.

Define Metrics & Specifications

• Design KPI trees and define metric intent.
• Specify requirements for Analytics Engineers to implement certified, production-grade data products.
• Define tracking plans for instrumentation.
• Specify dashboard requirements and acceptance criteria.
• Ensure data capture supports decision-making needs.

Partner Across the Business

• Collaborate with Product Managers, Commercial leaders, Analytics Engineers, and Marketers.
• Lead problem-framing sessions.
• Challenge assumptions and reframe vague requests into testable hypotheses.
• Bring analytical rigour to high-stakes discussions at the Director level.

Tackle Ambiguity

Super moves fast. The questions won’t always be clear. You’ll bring structure to chaos by translating broad business challenges into sharp analytical problems with measurable outcomes.

What We’re Looking For

Technical Mastery

• Advanced statistical methods & causal inference: A/B testing, confidence intervals, regression, quasi-experimental designs (difference-in-differences, synthetic controls, regression discontinuity), and an understanding of CUPED and variance reduction techniques
• SQL proficiency for exploratory analysis and data validation (we use Snowflake). Enough to spec requirements for Analytics Engineers. Optimisation expertise is not required at this level.

Decision Science Mindset

A track record of producing decision memos, strategy recommendations, or business cases that measurably influenced product and commercial strategy. You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.

Executive Communication

You excel at transforming complex causal analyses into clear, compelling narratives. You can distil findings into “so what” recommendations for Directors and other Commercial Stakeholders, making evidence accessible and actionable for strategic decision-making.

Commercial & Product Acumen

You don’t just crunch numbers. You understand how data connects to business outcomes, product design, and customer behaviour.

Proactive Problem Framing

You don’t wait for perfectly-scoped requests. You reframe vague asks, propose alternative hypotheses, and drive analytical roadmaps based on business priorities. You’re comfortable with ambiguity and bias toward “what should we do?” over “what happened?”.

Proven Track Record

Minimum 5+ years of relevant experience in analytics, data science, or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth through causal analysis and experimentation.

The Role

At Super, data isn’t a support function. It’s at the heart of every major decision we make.

As a Senior Commercial Data Scientist, you’ll operate at the intersection of product and strategy, owning decision-making, problem framing, and hypothesis generation. Your work won’t sit in slide decks. It will directly shape how millions of customers engage with our products.

This is a role for a very special kind of data scientist: someone who loves hard problems, thrives in ambiguity, and gets energised by moving from messy questions to clear decisions that drive strategy.

You’ll be expected to not just report what happened, but to uncover why through causal inference, anticipate what’s next, and produce decision memos that influence what we should do about it.

You’ll work in close partnership with Analytics Engineers, who build and maintain production data products. Your role is to define what needs to be measured and why, while AE ensures scalable, trustworthy data infrastructure.

What You’ll Do

Be the Decision Engine

• Run deep-dive analyses into customer behaviour, product usage, and commercial performance.
• Go beyond surface-level metrics to uncover causal drivers behind phenomena using rigorous statistical methods.
• Distinguish correlation from cause-and-effect.

Shape Strategy with Data

• Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions.
• Design and analyse experiments, including A/B tests and quasi-experiments.
• Deliver decision memos that change the course of decisions, with quantified impact ranges and clear “so what” guidance for Directors.

Define Metrics & Specifications

• Design KPI trees and define metric intent.
• Specify requirements for Analytics Engineers to implement certified, production-grade data products.
• Define tracking plans for instrumentation.
• Specify dashboard requirements and acceptance criteria.
• Ensure data capture supports decision-making needs.

Partner Across the Business

• Collaborate with Product Managers, Commercial leaders, Analytics Engineers, and Marketers.
• Lead problem-framing sessions.
• Challenge assumptions and reframe vague requests into testable hypotheses.
• Bring analytical rigour to high-stakes discussions at the Director level.

Tackle Ambiguity

Super moves fast. The questions won’t always be clear. You’ll bring structure to chaos by translating broad business challenges into sharp analytical problems with measurable outcomes.

What We’re Looking For

Technical Mastery

• Advanced statistical methods & causal inference: A/B testing, confidence intervals, regression, quasi-experimental designs (difference-in-differences, synthetic controls, regression discontinuity), and an understanding of CUPED and variance reduction techniques
• SQL proficiency for exploratory analysis and data validation (we use Snowflake). Enough to spec requirements for Analytics Engineers. Optimisation expertise is not required at this level.

Decision Science Mindset

A track record of producing decision memos, strategy recommendations, or business cases that measurably influenced product and commercial strategy. You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.

Executive Communication

You excel at transforming complex causal analyses into clear, compelling narratives. You can distil findings into “so what” recommendations for Directors and other Commercial Stakeholders, making evidence accessible and actionable for strategic decision-making.

Commercial & Product Acumen

You don’t just crunch numbers. You understand how data connects to business outcomes, product design, and customer behaviour.

Proactive Problem Framing

You don’t wait for perfectly-scoped requests. You reframe vague asks, propose alternative hypotheses, and drive analytical roadmaps based on business priorities. You’re comfortable with ambiguity and bias toward “what should we do?” over “what happened?”.

Proven Track Record

Minimum 5+ years of relevant experience in analytics, data science, or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth through causal analysis and experimentation.

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

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.

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

As Senior UX Research Manager at Super, you will own and scale a high-impact research function that sits at the heart of every major product decision. This is not a purely strategic or administrative role - we are looking for a hands-on research leader who can manage and grow a large team while simultaneously being a credible, practicing researcher.

You will report to the Research Director and have a direct seat at the executive table, shaping product strategy through the voice of the user. You will be expected to leverage AI tooling to transform how research is conducted, synthesized, and actioned across the organisation. This role defines the future of UX Research at Super.

What You Will Own

Strategic Research Leadership

• Define and own the multi-year UX research strategy aligned to Super's product and business goals across sports betting, gaming, and payments verticals.
• Translate ambiguous business challenges into crisp research programmes that generate confident executive decisions - from market expansion and feature prioritisation to onboarding flows and live betting experiences.
• Build and maintain a research roadmap that balances generative discovery, evaluative testing, and longitudinal tracking at scale.
• Represent research at the executive and C-suite level, presenting insights that drive resource allocation, product pivots, and go-to-market strategy.

Large-Team Hands-On Management

• Directly manage and grow a team of 6-8 UX researchers across seniority levels (junior through staff), spanning qual, quant, and mixed-methods disciplines.
• Grow junior managers in both UX Research and Market Research
• Maintain a hands-on presence: you conduct research yourself, review screeners and discussion guides, and are present in sessions - not only in deck reviews.
• Build a culture of craft and rigor; personally mentor researchers on methodology selection, analysis quality, and storytelling.
• Own hiring, performance management, career development frameworks, and team structure - adapting org design as the team scales.
• Create psychological safety and high-output norms simultaneously: a team that ships great research fast and keeps raising the quality bar.

AI-Driven Research Operations

• Lead the transformation of Super's research workflows through AI: identify, pilot, and embed AI tools for participant recruitment, auto-transcription and synthesis, pattern recognition across data sets, and accelerated insight generation.
• Champion AI-assisted analysis (e.g., LLM-powered thematic coding, sentiment analysis across user feedback pools) to reduce time-to-insight without sacrificing rigour.
• Establish responsible AI use guidelines for research — ensuring synthetic data, simulated users, and AI-generated summaries are used critically and transparently.
• Partner with data science and analytics to build continuous research intelligence pipelines that surface user signals in near-real-time.
• Stay ahead of the curve on AI-native research methods (e.g., conversational research agents, automated usability benchmarking) and make evidence-based bets on adoption.

Executive Decision Enablement

• Operate as a trusted advisor and thought partner to the VPs Product, and VP Design - shaping strategic decisions with user evidence before options narrow.
• Design and deliver research artefacts calibrated for executive consumption: crisp, opinionated, and actionable - not exhaustive reports, but decision-accelerating briefs.
• Build a culture of evidence-based decision-making across Product, Engineering, Marketing, and Commercial teams by embedding research touchpoints in planning and OKR cycles.
• Proactively identify decisions being made without research and intervene diplomatically with the right methodology at the right fidelity.

Research Practice & Infrastructure

• Build and own the research operations infrastructure: panel management, vendor relationships, consent frameworks, data governance, and tooling stack (e.g., Dovetail, UserZoom, Lookback, Maze).
• Establish a shared research repository that makes insights discoverable and reusable across product teams.
• Develop research democratisation programmes — training product managers and designers in appropriate self-serve methods while protecting methodological integrity.
• Define quality standards and peer-review practices that elevate the output of every researcher on the team.

What We Are Looking For

Essential Experience

• 10+ years of UX research experience in high-growth product environments, with at least 5 years in a people management role.
• Demonstrated experience managing large research teams (6+ direct and indirect reports) in a fast-paced, matrixed organisation.
• Proven track record of conducting and leading both qualitative and quantitative research — you are as comfortable running a contextual inquiry as you are designing a quant survey instrument.
• Experience presenting research to C-suite and board-level stakeholders and influencing major product or business decisions.
• Hands-on experience implementing AI tooling in research workflows — not just awareness, but actual deployment and change management.
• Strong command of the full research methods toolkit: ethnographic research, diary studies, usability testing, concept testing, conjoint analysis, surveys, behavioural analytics, and more.

Skills & Mindset

• Hands-on by default: You don't delegate everything. You know what good research looks like because you still do it.
• Executive presence: You can distill six months of research into a three-slide brief that changes a product direction.
• AI-native: You have moved beyond experimenting with AI tools and are actively building AI into your team's operating model.
• Systems thinker: You see research not as isolated studies but as an interconnected evidence system that continuously informs strategy.
• People developer: You have a track record of researchers growing significantly under your leadership.
• Commercially literate: You connect user insights to business outcomes — revenue, retention, conversion, and lifetime value — and speak that language fluently to non-research stakeholders.
• Comfortable with ambiguity: You thrive in environments where the brief is unclear, the timeline is compressed, and the stakes are high.

Nice to Have

• Experience in betting, gaming, fintech, or other high-velocity consumer product environments.
• Academic background in HCI, Psychology, Cognitive Science, Sociology, or a related human behaviour field.
• Experience building research practices from scratch or in significant transformation phases.
• Fluency in data tools (SQL basics, Tableau, Amplitude, Mixpanel) to triangulate behavioural with attitudinal data.
• Experience with internationalisation research across multiple markets and cultures.

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.

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

The Role

At Super technologies, data isn’t a support function, it’s at the heart of every major decision we make. As a Senior Scientist, you’ll operate at the intersection of product, commercial, and marketing strategy. Your analyses won’t sit in slide decks; they’ll directly shape how millions of customers engage with our products.

This is a role for very special kind of analyst: who love hard problems, thrive in ambiguity, and get energized by moving from messy data to clear insights that drive strategy. You’ll be expected to not just report what happened, but uncovering why, anticipating what’s next, and influencing what we should do about it.

What You’ll Do

• Be the Decision Engine: Run deep-dive analyses into customer behaviour, product usage, and commercial performance. Go beyond surface-level metrics to uncover the drivers behind the phenomenon.
• Shape Strategy with Data: Influence product roadmaps, commercial tactics, and marketing strategies by framing the right questions, running experiments (A/B testing, causal inference etc.), and delivering insights that change the course of decisions.
• Automate Intelligence: Build scalable dashboards, reporting systems, and data tools that enable teams across Superbet to make smarter, faster, data-driven decisions.
• Partner Across the Business: Collaborate with Product Managers, Commercial leaders, Engineers, Designers, and Marketers. You won’t just answer questions, you’ll help define them, challenge assumptions, and bring analytical rigor to high-stakes discussions.
• Tackle Ambiguity: Superbet moves fast. The questions won’t always be clear. You’ll be the one who can bring structure to chaos, translating broad business challenges into sharp, analytical problems.

What We’re Looking For

• Technical Mastery: SQL fluency (we use Snowflake) is a non-negotiable (but, we are open if you can make data talk through other languages!). You should be equally comfortable working with complex data as you are doing deep inquiry through statistical/ML methods and bringing them to life in dashboards (we use Tableau).
• Data Storytelling: You excel at transforming complex analyses into clear, compelling narratives. You can communicate insights effectively to both technical and non-technical stakeholders, making data accessible and actionable for decision-making.
• Commercial & Product Acumen: You don’t just crunch numbers; you understand how data connects to business outcomes, product design, and customer behavior.
• Bias for Impact: You care less about perfect models and more about driving measurable change. Your analyses are only successful if they move the needle.
• Proven Track Record: Previous experience in analytics and/or product data science roles (ideally in product or commercial domains) where you’ve directly influenced strategy and growth.
• Education: Degree in Data Science, Statistics, Economics, Computer Science/Engg., Mathematics, or a related quantitative field OR equivalent work experience.
• Years of Experience: We are hiring for roles with at least 2+ years of relevant experience.

Why Join Us?

• High Impact
  • Your datasets will be used daily by teams making product decisions, running experiments, and driving performance.
• Real Scale, Real Problems
  • Handle serious data volumes. We’re talking millions of events per day, multiple sources, and zero fluff.
• Freedom to Shape
  • Influence our data architecture, tooling, and best practices. You're not just implementing—you’re building.
• Solid Benefits
  • Competitive compensation & performance-based bonuses
  • Open vacation policy & hybrid work flexibility
  • Health support, wellness perks & team social budget

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.