We are one of the largest sports betting operators in the region making 1000+ location networks work across multiple geographies. If you ever wanted to see how software can handle 22 million bets per month - why not join us?

We're looking for someone who

• Holds at least a Bachelor's Degree in Computer Science or a related field
• Has 5+ years of experience building high-quality software and values strong engineering practices like code reviews, CI/CD, and design documents
• Excels at writing clean, maintainable, and well-tested code with a focus on performance and scalability
• Embraces best practices in software engineering, such as comprehensive code reviews and thoughtful design documentation
• Is passionate about delivering high-quality solutions that anticipate and exceed customer needs
• Enjoys working in a collaborative team environment and communicates effectively with others

Bonus points for

• Experience with our tech stack/tools: Golang, Kubernetes, Kafka
• A passion for cloud technologies
• Familiarity with AWS services
• Experience in the betting/gaming industry

What you will be doing

• Contributing directly to the design and code of our platform;
• Optimizing the platform to support product features more efficiently;
• Focusing on ensuring the platform is stable and reliable;
• Supporting platform expansion into new markets and maintaining a stable hosting environment;
• Enabling traders to define what we map to our external offerings;
• Impacting product health in terms of scalability, speed, quality, and flexibility;
• Maintaining low latency and high success rates for the platform, directly improving user experience;
• Conducting design and code reviews and providing mentorship to other team members;
• Continuously iterating to engage customers and bring excitement to the Sports Betting and Gaming industry.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Think of a product. Like lean, mean software. For sports betting. With the best possible real-time solutions. Now think of innovating the testing process. Stopping bugs from reaching production. Paying special attention to how and what is delivered. Directly tailoring the experience for tens of thousands of people daily. Sounds interesting?

What You’ll Be Doing:

• Be responsible for designing, implementing, and managing automated tests across the product suite
• Design and implement comprehensive test automation solutions that encompass web applications, web services (microservices), and native apps. Ensure coverage across various testing types, including UI testing, API testing, and others, to support robust quality assurance practices
• Collaborate with business stakeholders to define acceptance criteria for software projects
• Be jointly responsible for the maintenance and quality of codebases and infrastructure
• Issue Investigation and Reporting
• Quality Control: Ensure we have vital checks on all our products (metrics, health checks) dashboards, ensure critical business scenarios are covered and automate them.
• Making sure tests run in Continuous Integration

We Are Looking for Someone Who:

• Has a minimum of Bachelor’s degree in Computer Science or a related discipline
• Is highly proficient in Functional or Object-oriented programming
• Has strong understanding of QA processes and demonstrated experience in defining and implementing test designs from scratch
• Has extensive experience with test automation tools (Selenium, Cypress, Playwright etc.)
• Has extensive experience writing backend tests (API, unit, database) and testing RESTful services using tools such as Postman or SoapUI
• Has understanding of Non-Functional testing, especially Load and Performance testing
• Prefers a shift-left testing approach

Nice to Have:

• ISTQB certification
• Experience with BDD (Behaviour Driven Development)
• Knowledge of Ruby or JavaScript
• Experience using Xray or similar Test Management tool
• Experience with event-driven architecture (Kafka, AWS, Docker etc.), preferably in a Product environment

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

Overview

As a Staff Data Product Manager for the Analytics Platform, you will own the vision and roadmap for our core data foundation, primarily powered by Snowflake. Your mission is to bridge the "Perception vs. Reality" gap: while our platform is technically robust (with minimal incidents in 2025), users often find data hard to use or unclear.
You will define the "what" and "why" of our platform , ensuring it transitions from a reactive service to a strategic partner that empowers every team at Super to leverage data and AI capabilities at scale.

Key responsibilities

Product strategy & vision

• Own and articulate the product strategy and long-term vision for the Analytics Platform by defining the end-to-end analytical product lifecycle —- from data producer contract management and quality guardrails to downstream data consumers, their access patterns, and measurable value realisation.
• Develop a long-term vision for the Analytics Platform, aligning with broader data-driven objectives.
• Stay ahead of industry trends in cloud warehousing, data modeling, and emerging AI technologies.
• Propose and explore new ways of utilizing Snowflake to leverage AI capabilities and drive business value.

User research & advocacy

• Define and continuously evolve a clear measurement framework for Analytics Platform usability and adoption; use it to enable data-driven decisions with platform leaders and to directly shape roadmap priorities based on measurable impact.
• Deeply investigate actual customer needs, workflows, and pain points to eliminate "blind spots" in platform adoption.
• Address the gap between technical uptime and user perception by ensuring data is intuitive, clear, and reliable.
• Champion a user-centric culture, transforming how technical and business teams interact with our data models.

Roadmap & stakeholder management

• Build and maintain a prioritized product roadmap, balancing operational excellence with strategic initiatives.
• Collaborate with Product, Marketing, and Data Science to ensure Analytics platform is focused on most impactful initiatives across all areas

Strategic integration

• Partner with Product teams to ensure the Analytics Platform is a first-class citizen in the development lifecycle, not an afterthought.
• Partner with the Analytics Platform and Data leadership to transform high-level objectives into vision, direction and roadmap for a scalable, reliable technical platform.

Execution & delivery

• Translate business goals into well-defined problem statements, user stories, and acceptance criteria.
• Manage the development cycle in an Agile environment, providing clarity on priorities and monitoring progress.
• Ensure every initiative has a defined "Problem to Solve" and clear success measurement.

Qualifications

1. Education & experience

• Bachelor’s or Master’s degree in Business, Computer Science, Data Science, or a related field.
• 6–8+ years of product management experience, specifically with data products or analytics platforms.

2. Technical & domain expertise

• Strong familiarity with Analytics databases (e.g Snowflake, BigQuery, Redshift), ETL pipelines, DWH concepts and BI tools.
• Ability to convert complex technical concepts into clear business value.
• Proven track record in leading cross-functional teams

3. Strong differentiators

• Previous experience driving large-scale data product initiatives from ideation to launch
• Experience in entertainment, online gaming, or sports betting industries.

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.

We are one of the largest sports betting operators in the region making 1000+ location networks work across multiple geographies. If you ever wanted to see how software can handle 22 million bets per month - why not join us?

We're looking for someone who

• Holds at least a Bachelor's Degree in Computer Science or a related field
• Has 5+ years of experience building high-quality software and values strong engineering practices like code reviews, CI/CD, and design documents
• Excels at writing clean, maintainable, and well-tested code with a focus on performance and scalability
• Embraces best practices in software engineering, such as comprehensive code reviews and thoughtful design documentation
• Is passionate about delivering high-quality solutions that anticipate and exceed customer needs
• Enjoys working in a collaborative team environment and communicates effectively with others

Bonus points for

• Experience with our tech stack/tools: Golang, Kubernetes, Kafka
• A passion for cloud technologies
• Familiarity with AWS services
• Experience in the betting/gaming industry

What you will be doing

• Contributing directly to the design and code of our platform;
• Optimizing the platform to support product features more efficiently;
• Focusing on ensuring the platform is stable and reliable;
• Supporting platform expansion into new markets and maintaining a stable hosting environment;
• Enabling traders to define what we map to our external offerings;
• Impacting product health in terms of scalability, speed, quality, and flexibility;
• Maintaining low latency and high success rates for the platform, directly improving user experience;
• Conducting design and code reviews and providing mentorship to other team members;
• Continuously iterating to engage customers and bring excitement to the Sports Betting and Gaming industry.

We are one of the largest sports betting operators in the region making 1000+ location networks work across multiple geographies. If you ever wanted to see how software can handle 22 million bets per month - why not join us?

We're looking for someone who

• Holds at least a Bachelor's Degree in Computer Science or a related field
• Has 5+ years of experience building high-quality software and values strong engineering practices like code reviews, CI/CD, and design documents
• Excels at writing clean, maintainable, and well-tested code with a focus on performance and scalability
• Embraces best practices in software engineering, such as comprehensive code reviews and thoughtful design documentation
• Is passionate about delivering high-quality solutions that anticipate and exceed customer needs
• Enjoys working in a collaborative team environment and communicates effectively with others

Bonus points for

• Experience with our tech stack/tools: Golang, Kubernetes, Kafka
• A passion for cloud technologies
• Familiarity with AWS services
• Experience in the betting/gaming industry

What you will be doing

• Contributing directly to the design and code of our platform;
• Optimizing the platform to support product features more efficiently;
• Focusing on ensuring the platform is stable and reliable;
• Supporting platform expansion into new markets and maintaining a stable hosting environment;
• Enabling traders to define what we map to our external offerings;
• Impacting product health in terms of scalability, speed, quality, and flexibility;
• Maintaining low latency and high success rates for the platform, directly improving user experience;
• Conducting design and code reviews and providing mentorship to other team members;
• Continuously iterating to engage customers and bring excitement to the Sports Betting and Gaming industry.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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.

As a Senior 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 4+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

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 a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

As a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

As a 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.

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:

• Partner with product and engineering to identify and execute machine learning use cases that deliver measurable impact
• Design, build, and iterate on machine learning solutions (e.g., classifiers, regressors, ranking/retrieval, and rule-based components)
• Contribute across the ML lifecycle: data exploration, feature engineering, training, evaluation, deployment, and monitoring
• Implement reliable training/inference pipelines and help improve reproducibility, testing, and observability
• Communicate model behavior, trade-offs, and results clearly to both technical and non-technical stakeholders
• Contribute to team standards: code quality, documentation, experimentation hygiene, and responsible ML practices

We're looking for someone with:

• Bachelor’s degree in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field (Master’s a plus)
• 2+ years of industry experience building and deploying ML systems
• Solid proficiency in Python and familiarity with common ML libraries (e.g., PyTorch, XGBoost) and SQL
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies
• Demonstrated ability to write maintainable, tested code, participate in code reviews, and follow engineering best practices
• Strong problem-solving skills with the ability to break down ambiguous problems into scoped tasks and deliver iteratively

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

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

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