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.

In Superbet, the Quant team is responsible for developing the models and tools required for trading a wide range of sports. We aim to provide the best betting experience to our current customers and those we will acquire during our expansion across the globe. This will mean producing prices for the full range of markets that our customers expect, same-game accumulators, 100% betting availability, and 100% cash out. We see the Quant team as a major driver within this process and want to talk to people who believe they could help us become one of the leading betting brands worldwide.

As a Senior Quant, we would like you to play a big role in driving this process. Use your industry experience to produce Player Prop prices, solve the related contingencies required for same-game accumulators, maximise uptime and bring ideas about products and best-in-class modelling methodologies with you.

We are looking for someone who:

• Has experience delivering in-house models within the betting industry
• Can help us produce market-leading bet builder / same game acca solutions across multiple sports
• Would like to guide proprietary modelling of non-core markets
• Has experience dealing with large data sets and feeds
• Wants to become a key part of a fast-growing Quant team and company
• Has excellent communication skills, able to understand and translate complex technical information to others
• Feels comfortable collaborating with various teams
• Has a strong work ethic with a drive for completing high-quality work

Bonus points if you have:

• Experience in American Sports modelling
• Bet Builder / Same game accumulator modelling
• Experience in eSports modelling
• Golang experience

What you'll be doing:

• Develop mathematical and statistical models which will price the core and derivative markets for those Sports
• Produce related contingency modelling solutions
• Provide performance analysis through backtesting and optimizing model output
• Collect and analyse market data in order to aid model development
• Create and price new products to supplement existing markets/sports
• Build trader tooling in order to maximize the efficiency of the trading operation
• Collaborate with engineering resources to enable seamless integration of any provided solutions

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Overview

As a Senior Data Product Manager – Experimentation, you will own the vision, strategy, and roadmap of our internal experimentation platform. Your primary focus will be defining “what” we build and “why”—ensuring our teams have robust, intuitive tools for A/B testing, audience segmentation, feature flag management, and data-driven decision-making. Through close collaboration with Engineering, Data Science, Marketing, and Product teams, you will champion a hypothesis-driven culture, transforming how we learn, iterate, and innovate at scale. Your work will empower every team at SuperBet to rapidly experiment, reduce time-to-insight, and drive measurable business impact.

Key responsibilities

1. Product strategy & vision

• Develop a clear, long-term product vision for the Experimentation Platform, aligning with the broader data-driven objectives.
• Stay attuned to industry best practices, academic research, and emerging technologies to keep our platform at the cutting edge.

2. Defining the “What” and “Why”

• Translate business goals and user requirements into well-defined problem statements, expected business impact, and success metrics.
• Advocate for the importance of hypothesis-driven development, evangelizing experimentation methodologies across the organization.

3. Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap for experimentation, balancing quick wins with strategic, long-term initiatives.
• Collaborate with cross-functional stakeholders (Product, Marketing, Data Science, Engineering) to gather feedback, refine requirements, and drive alignment.

4. Cross-functional collaboration

• Partner closely with the Senior Engineering Manager to transform high-level product objectives into a scalable, reliable, and efficient technical platform.
• Collaborate with Data Scientists and Analysts to define statistical engines, experiment design templates, and consistent KPI frameworks.
• Work with Marketing and Product teams to ensure the experimentation platform meets diverse needs—ranging from audience segmentation to feature flagging and surveys.

5. Execution & delivery

• Clearly communicate product requirements, user stories, and acceptance criteria to engineering teams.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure each initiative launches with a defined Problem to Solve, Business Impact, and Success Measurement, tracking progress to inform continuous improvement.

6. Performance & impact tracking

• Define robust product success metrics (adoption rates, number of experiments run, time-to-insight, etc.) and implement tracking mechanisms.
• Analyze usage data and experiment results to validate assumptions, identify gaps, and inform product enhancements.
• Champion experimentation quality measurements—ensuring teams follow best practices and extract meaningful insights.
• Work with user communities to collect feedback, refine feature requirements, and iterate on platform improvements.

7. Domain expertise & thought leadership

• Serve as the in-house expert on experimentation methodologies, statistical significance, confidence intervals, and advanced testing frameworks.
• Lead initiatives like an Experimentation Embassy, workshops, and knowledge-sharing sessions to promote best practices across the company.

8. Communication & evangelism

• Own the narrative around experimentation—communicating platform updates, success stories, and impact to both technical and non-technical audiences.
• Continuously evangelize the power of a hypothesis-driven, data-informed approach within the organisation, aligning executives and teams on key objectives.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, Statistics, or a related field (or equivalent practical experience).
• 6–8+ years of product management experience, ideally with a focus on data products, analytics, or experimentation platforms.

2. Technical & domain expertise

• Strong familiarity with A/B testing, multivariate testing, feature flag management, and audience segmentation.
• Understanding of statistical methods (confidence intervals, p-values, hypothesis testing) and ability to collaborate with data scientists on experiment designs.
• Exposure to data infrastructure, ETL pipelines, BI tools, and relevant technologies.

3. Product management skills

• Proven track record in leading cross-functional teams (Engineering, Data Science, UX) using Agile methodologies.
• Ability to convert complex data or statistical concepts into clear business value and actionable product requirements.
• Skilled in developing roadmaps, facilitating stakeholder alignment, and prioritizing high-impact features.

4. Strong differentiators

• Hands-on experience building experimentation platforms, customer segmentation systems, or ML evaluation frameworks.
• Previous work in entertainment, online gaming, or sports betting industries, especially around experimentation and user experience improvements.
• Previous experience driving large-scale data product initiatives, from ideation to launch.

Super Technologies is offering an exciting Erasmus+ traineeship programme based in either London or Madrid. This is a unique opportunity to gain hands-on experience in a fast-paced, international environment while contributing to impactful business projects. We are looking for motivated, curious, and driven individuals who are eager to develop their skills and gain real-world experience aligned with their career goals.

Areas of Impact:

Applicants are encouraged to indicate their preferred department based on their interests and career aspirations. Current opportunities include:

International Market Expansion
Support our global growth strategy by conducting market research, building financial business cases, and evaluating strategic expansion opportunities.

Sports Quant
Work at the intersection of sports and quantitative analysis. Use programming languages such as Python, R, or Matlab to analyse data and develop predictive models.

Data & Insights
Play a key role in driving data-led decision-making. Build data pipelines, create dashboards, and transform complex datasets into actionable business insights.

Please note: Final placement will be determined based on both your profile and business needs.

What you'll be doing:

• Collaborate with cross-functional teams on real business projects
• Conduct research, analysis, and problem-solving within your chosen area
• Contribute to ongoing strategic initiatives
• Present findings and insights to stakeholders
• Continuously learn and apply new tools, techniques, and methodologies

What we are looking for:

• Currently enrolled in a relevant university programme eligible for Erasmus+
• Strong academic background aligned with your chosen department
• Excellent communication and collaboration skills
• Proactive mindset with a willingness to learn
• For Data & Insights: preference for candidates with technical backgrounds (e.g. engineering, computer science, statistics, or similar)

Application Process

• Submit an updated CV
• Provide a short motivation letter
• Include any additional documents required by your university

Shortlisted candidates will be invited to interview and discuss potential department placement.

Programme Structure

This is a structured three-month traineeship combining:

• On-the-job experience
• Formal training
• Ongoing mentorship and feedback

At the end of the programme, trainees will present their work and key learnings to the team.

Future Opportunities

Successful trainees may be considered for long-term career opportunities within Super Technologies.

Why Join Us?

• Gain hands-on experience in a dynamic, international business
• Work on meaningful, high-impact projects
• Develop both technical and professional skills
• Receive mentorship from experienced professionals
• Build a strong foundation for your future career

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As the Director of P&C Strategy & Governance, you are the architect of our global People transformation and the engine room of our strategic execution. Reporting to the VP, HRBP, you will lead a high-performing PMO team to bridge the gap between ambitious vision and measurable business impact. This is a high-visibility leadership role designed for a heavy-hitter who thrives on driving discipline, rigour, and velocity. You won’t just manage a portfolio; you will orchestrate the global People agenda, ensuring every initiative is prioritised for value, aligned cross-functionally, and delivered with precision.

In this role, you will own the executive governance framework and act as a critical partner to the Chief of Staff and Business Transformation offices. We offer a dynamic, multi-country landscape where you can build from scratch, evolve existing frameworks, and directly shape the future operating model of People & Culture globally.

What you’ll be doing:

• Architect and lead the annual P&C OKR development process, transforming high-level people strategy into a consolidated, execution-ready global portfolio.
• Lead quarterly and annual prioritization cycles, ensuring human and financial capital are ruthlessly aligned with the business strategy and budget.
• Establish rigorous standards for initiative success, ensuring every project carries a clear business case, defined ROI, and measurable impact metrics.
• Define the architectural distinction between Business-as-Usual (BAU) and high-impact strategic projects, establishing bespoke governance and SteerCo frameworks for each.
• Design and oversee a world-class Go-to-Market framework for all People initiatives, ensuring seamless adoption across diverse global business units.
• Partner with Executive Communications to ensure the sequencing of people initiatives tells a cohesive story that resonates with the workforce.
• Act as the guardian of "change capacity," proactively identifying risks related to change fatigue, initiative overload, and audience saturation.
• Serve as the primary strategic link between P&C and the Chief of Staff, Central Transformation Office, and Finance, ensuring People initiatives are woven into the broader corporate fabric.
• Masterfully navigate complex cross-functional dependencies, proactively mitigating execution risks before they impact the business.
• Oversee the development of high-stakes Board and Executive-level memos, ensuring all P&C proposals are structured, financially sound, and decision-ready for the CHRO and Leadership Team.
• Define and continuously evolve the global P&C project management methodology, shifting the culture toward a "delivery-first" mindset.
• Provide executive-level transparency into portfolio health, budget utilization, and risk profiles, utilizing data to drive high-level steering decisions.
• Strategically manage P&C capacity, providing the VP and LT with the insights needed to make critical trade-offs in resource allocation.
• Lead, coach, and elevate a team of Senior Project Managers and Analysts, fostering a culture of high performance and professional growth.
• Act as a center of excellence for the wider HR function, building project management maturity and execution discipline across all People teams.

What you’ll bring:

• 10+ years of progressive experience in program and portfolio management, with a proven track record of leading large-scale global transformations.
• Significant experience in management consulting or internal strategy, moving beyond design to lead successful global deployment.
• Proven ability to lead and develop high-performing teams of senior project managers and specialists.
• Exceptional ability to translate complex portfolio data into clear, data-driven narratives for the CHRO and Board.
• Advanced influencing skills to navigate ambiguity and build credibility within a high-growth, matrixed C-suite environment.
• A seasoned leader capable of driving executive consensus on competing priorities and the long-term People strategy.
• Proven ability to build GTM frameworks, governance models, and P&C roadmaps from scratch.
• Strong financial literacy with a focus on capacity modeling, budget oversight, and value realization.
• Expert in PPM methodologies and tools (e.g., Jira, Asana, Notion) to drive organizational transparency and reporting at scale.
• A rare blend of long-term strategic vision and a disciplined, delivery-focused mindset.

As the Director of P&C Strategy & Governance, you are the architect of our global People transformation and the engine room of our strategic execution. Reporting to the VP, HRBP, you will lead a high-performing PMO team to bridge the gap between ambitious vision and measurable business impact. This is a high-visibility leadership role designed for a heavy-hitter who thrives on driving discipline, rigour, and velocity. You won’t just manage a portfolio; you will orchestrate the global People agenda, ensuring every initiative is prioritised for value, aligned cross-functionally, and delivered with precision.

In this role, you will own the executive governance framework and act as a critical partner to the Chief of Staff and Business Transformation offices. We offer a dynamic, multi-country landscape where you can build from scratch, evolve existing frameworks, and directly shape the future operating model of People & Culture globally.

What you’ll be doing:

• Architect and lead the annual P&C OKR development process, transforming high-level people strategy into a consolidated, execution-ready global portfolio.
• Lead quarterly and annual prioritization cycles, ensuring human and financial capital are ruthlessly aligned with the business strategy and budget.
• Establish rigorous standards for initiative success, ensuring every project carries a clear business case, defined ROI, and measurable impact metrics.
• Define the architectural distinction between Business-as-Usual (BAU) and high-impact strategic projects, establishing bespoke governance and SteerCo frameworks for each.
• Design and oversee a world-class Go-to-Market framework for all People initiatives, ensuring seamless adoption across diverse global business units.
• Partner with Executive Communications to ensure the sequencing of people initiatives tells a cohesive story that resonates with the workforce.
• Act as the guardian of "change capacity," proactively identifying risks related to change fatigue, initiative overload, and audience saturation.
• Serve as the primary strategic link between P&C and the Chief of Staff, Central Transformation Office, and Finance, ensuring People initiatives are woven into the broader corporate fabric.
• Masterfully navigate complex cross-functional dependencies, proactively mitigating execution risks before they impact the business.
• Oversee the development of high-stakes Board and Executive-level memos, ensuring all P&C proposals are structured, financially sound, and decision-ready for the CHRO and Leadership Team.
• Define and continuously evolve the global P&C project management methodology, shifting the culture toward a "delivery-first" mindset.
• Provide executive-level transparency into portfolio health, budget utilization, and risk profiles, utilizing data to drive high-level steering decisions.
• Strategically manage P&C capacity, providing the VP and LT with the insights needed to make critical trade-offs in resource allocation.
• Lead, coach, and elevate a team of Senior Project Managers and Analysts, fostering a culture of high performance and professional growth.
• Act as a center of excellence for the wider HR function, building project management maturity and execution discipline across all People teams.

What you’ll bring:

• 10+ years of progressive experience in program and portfolio management, with a proven track record of leading large-scale global transformations.
• Significant experience in management consulting or internal strategy, moving beyond design to lead successful global deployment.
• Proven ability to lead and develop high-performing teams of senior project managers and specialists.
• Exceptional ability to translate complex portfolio data into clear, data-driven narratives for the CHRO and Board.
• Advanced influencing skills to navigate ambiguity and build credibility within a high-growth, matrixed C-suite environment.
• A seasoned leader capable of driving executive consensus on competing priorities and the long-term People strategy.
• Proven ability to build GTM frameworks, governance models, and P&C roadmaps from scratch.
• Strong financial literacy with a focus on capacity modeling, budget oversight, and value realization.
• Expert in PPM methodologies and tools (e.g., Jira, Asana, Notion) to drive organizational transparency and reporting at scale.
• A rare blend of long-term strategic vision and a disciplined, delivery-focused mindset.

As the Director of P&C Strategy & Governance, you are the architect of our global People transformation and the engine room of our strategic execution. Reporting to the VP, HRBP, you will lead a high-performing PMO team to bridge the gap between ambitious vision and measurable business impact. This is a high-visibility leadership role designed for a heavy-hitter who thrives on driving discipline, rigour, and velocity. You won’t just manage a portfolio; you will orchestrate the global People agenda, ensuring every initiative is prioritised for value, aligned cross-functionally, and delivered with precision.

In this role, you will own the executive governance framework and act as a critical partner to the Chief of Staff and Business Transformation offices. We offer a dynamic, multi-country landscape where you can build from scratch, evolve existing frameworks, and directly shape the future operating model of People & Culture globally.

What you’ll be doing:

• Architect and lead the annual P&C OKR development process, transforming high-level people strategy into a consolidated, execution-ready global portfolio.
• Lead quarterly and annual prioritization cycles, ensuring human and financial capital are ruthlessly aligned with the business strategy and budget.
• Establish rigorous standards for initiative success, ensuring every project carries a clear business case, defined ROI, and measurable impact metrics.
• Define the architectural distinction between Business-as-Usual (BAU) and high-impact strategic projects, establishing bespoke governance and SteerCo frameworks for each.
• Design and oversee a world-class Go-to-Market framework for all People initiatives, ensuring seamless adoption across diverse global business units.
• Partner with Executive Communications to ensure the sequencing of people initiatives tells a cohesive story that resonates with the workforce.
• Act as the guardian of "change capacity," proactively identifying risks related to change fatigue, initiative overload, and audience saturation.
• Serve as the primary strategic link between P&C and the Chief of Staff, Central Transformation Office, and Finance, ensuring People initiatives are woven into the broader corporate fabric.
• Masterfully navigate complex cross-functional dependencies, proactively mitigating execution risks before they impact the business.
• Oversee the development of high-stakes Board and Executive-level memos, ensuring all P&C proposals are structured, financially sound, and decision-ready for the CHRO and Leadership Team.
• Define and continuously evolve the global P&C project management methodology, shifting the culture toward a "delivery-first" mindset.
• Provide executive-level transparency into portfolio health, budget utilization, and risk profiles, utilizing data to drive high-level steering decisions.
• Strategically manage P&C capacity, providing the VP and LT with the insights needed to make critical trade-offs in resource allocation.
• Lead, coach, and elevate a team of Senior Project Managers and Analysts, fostering a culture of high performance and professional growth.
• Act as a center of excellence for the wider HR function, building project management maturity and execution discipline across all People teams.

What you’ll bring:

• 10+ years of progressive experience in program and portfolio management, with a proven track record of leading large-scale global transformations.
• Significant experience in management consulting or internal strategy, moving beyond design to lead successful global deployment.
• Proven ability to lead and develop high-performing teams of senior project managers and specialists.
• Exceptional ability to translate complex portfolio data into clear, data-driven narratives for the CHRO and Board.
• Advanced influencing skills to navigate ambiguity and build credibility within a high-growth, matrixed C-suite environment.
• A seasoned leader capable of driving executive consensus on competing priorities and the long-term People strategy.
• Proven ability to build GTM frameworks, governance models, and P&C roadmaps from scratch.
• Strong financial literacy with a focus on capacity modeling, budget oversight, and value realization.
• Expert in PPM methodologies and tools (e.g., Jira, Asana, Notion) to drive organizational transparency and reporting at scale.
• A rare blend of long-term strategic vision and a disciplined, delivery-focused mindset.

As an International Program Manager, you will be at the forefront of executing strategic programs to support market entries, platform migrations or significant regulatory changes. In addition, you will drive cross-area product initiatives that require collaboration across multiple product and technology teams.

This role is ideal for someone with solid program management foundations from a technology company who is eager to learn and grow within our organisation. If you're a structured yet adaptable professional who thrives in a dynamic and fast-paced environment, we’d love to hear from you!

We're looking for someone with:

• 5-10 years of experience in program or project management, preferably in tech, digital, or gaming industries.
• Exposure to complex projects involving multiple stakeholders; experience with market expansion, compliance, or re-platforming is a plus.
• Strong communication and interpersonal skills to foster collaboration across teams.
• Ability to structure and prioritise work in a fast-paced environment.
• A proactive and problem-solving mindset with a willingness to learn and adapt.
• Comfortable working with data to track program success and inform decision-making.

What you'll be doing

• Program execution & delivery: Manage end-to-end delivery of key initiatives, including expansion into new markets, compliance with evolving regulations, and major platform transitions.
• Cross team collaboration: Work closely with product, technology, compliance, operations, and commercial teams to ensure alignment and smooth execution of initiatives.
• Stakeholder management: Communicate progress, risks, and dependencies to internal and external stakeholders in a clear and structured manner.
• Process optimization: Support continuous improvements in our ways of working.
• Risk & issue management: Identify potential roadblocks early and proactively drive resolutions.
• Reporting & documentation: Maintain clear program tracking, status reports, and key performance updates.

As an International Program Manager, you will be at the forefront of executing strategic programs to support market entries, platform migrations or significant regulatory changes. In addition, you will drive cross-area product initiatives that require collaboration across multiple product and technology teams.

This role is ideal for someone with solid program management foundations from a technology company who is eager to learn and grow within our organisation. If you're a structured yet adaptable professional who thrives in a dynamic and fast-paced environment, we’d love to hear from you!

We're looking for someone with:

• 5-10 years of experience in program or project management, preferably in tech, digital, or gaming industries.
• Exposure to complex projects involving multiple stakeholders; experience with market expansion, compliance, or re-platforming is a plus.
• Strong communication and interpersonal skills to foster collaboration across teams.
• Ability to structure and prioritise work in a fast-paced environment.
• A proactive and problem-solving mindset with a willingness to learn and adapt.
• Comfortable working with data to track program success and inform decision-making.

What you'll be doing

• Program execution & delivery: Manage end-to-end delivery of key initiatives, including expansion into new markets, compliance with evolving regulations, and major platform transitions.
• Cross team collaboration: Work closely with product, technology, compliance, operations, and commercial teams to ensure alignment and smooth execution of initiatives.
• Stakeholder management: Communicate progress, risks, and dependencies to internal and external stakeholders in a clear and structured manner.
• Process optimization: Support continuous improvements in our ways of working.
• Risk & issue management: Identify potential roadblocks early and proactively drive resolutions.
• Reporting & documentation: Maintain clear program tracking, status reports, and key performance updates.

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.