Joining Busuu means being part of one of the top EdTech companies in the world, a multiple award-winner recognised for its innovation and impact in language learning.

Busuu’s vision is to empower people through languages. We are the world’s largest online community for language learning, with 120+ million registered users. We make learning a language easy by combining AI-powered courses with feedback from our global community of native speakers and lesson content designed for real life.

Busuu is part of the global Chegg family. Chegg is the leading student-first connected learning platform and a NYSE listed company.

Why this role is exciting

This is a rare opportunity to build a new capability from the ground up. You will work on high-visibility problems that sit at the intersection of data science, strategy, business performance, and AI transformation. You will partner directly with leadership, shape how the company measures itself, and build the operating intelligence that helpsBusuumake better decisions, faster.

• Build a neworganisationalintelligence capability in a company actively reshaping itself around AI.

• Work on problems with direct visibility to the General Manager, leadership team, and cross-functional heads.

• Designcutting-edgemeasurement systems, decision frameworks, and intelligence layers — not just dashboards.

• Operate across B2C, B2B, Product, Commercial, and AI initiatives, with broad influence on how the company runs.

• Combine deep analytical thinking withreal businessimpact in a role that is strategic, hands-on, and highly visible.

The role

We are hiring a Staff Data Scientist to leadOrganisationalIntelligence within Decision Intelligence. The mission of this role is to helpBusuuunderstand itself as a system: how performance is evolving, where transformation is working or failing, how teams should interpret signals across the business, and what leadership should do next.

This person will design the measurement architecture, synthesis, and business learning loops that connect data to decisions at company level. You will own the analytical foundation behind monthly and quarterly business reviews, define how transformation is measured,establishtrusted business metric definitions, and help turn AI governance into an operating reality.

What you will do

• Design and run the analytical architecture behind Monthly and Quarterly Business Reviews, ensuring they lead to decisions rather than reporting theatre.

• Create the company-level performance narrative bysynthesisingsignals across B2C, B2B, Product, Lifecycle, Commercial, Finance, and AI initiatives.

• Build andoperationalisethe framework used to measureorganisationaland AI transformation, including efficiency, effectiveness, and human impact.

• Owncanonicaldefinitions for the company’s most important business metrics and create a robust process for resolving definition disputes across teams.

• Design maturity models and business learning loops that helpBusuuimprove how it makes decisions over time.

• Partner with Data Engineering and analytics teams to translate business logic into trusted semantic and reporting layers.

• Act as the operating lead for AI governance by preparing decision papers, risk assessments, governance artefacts, and post-incident reviews.

• Combine quantitative analysis, qualitative insight, and competitor signals into a coherent view that leadership can use toprioritiseaction.

Jobs to be done

• Make it easy for leadership to understand company performance at a system level.

• Turn fragmented business and product signals into a clear point of view on what matters most.

• Create trusted measurement standards so teams can debate decisions without debating the basics.

• Build repeatable ways to measureorganisationalchange and AI transformation.

• Improve the quality and speed of company-level decision-making through better synthesis and sharper business framing.

• HelpBusuumove from pockets of insight to a durableorganisationalintelligence capability.

What success looks like

Within3-6 months

• Business reviews are running through a more consistent and decision-oriented structure.

• Transformation measurement isestablishedandbeing usedin leadership conversations.

• Quantitative, qualitative, and competitor synthesisisembedded into leadership review cycles.

• Definitionchanges and disputes are managed through a clear governance process.

• A maturity model is in use to guide improvement in data, decision-making, and AI adoption.

Within 12 months

• Busuuhas a credibleorganisationalintelligence layer used by leadership as a default lens on performance.

• Executive conversations are more evidence-led, cross-functional, and forward-looking.

• AI governance isoperationalisedearly in decision-making rather than applied after the fact.

• This role isrecognisedas a key strategic voice on performance, transformation, and decision quality.

What we are looking for - Required experience

• 8+ years of experience in data science, analytics, business intelligence, strategy, consulting, or a similar function in a scaled digital, SaaS, consumer tech, subscription, or EdTech business.

• Strong experience translating analysis into business decisions, preferably with exposure to executive or leadership-level reporting.

• Experience designing performance frameworks, KPI systems, company scorecards, business review processes, or equivalent decision-support systems.

• Strong SQL skills and confidence working directly with complex datasets.

• Ability to move fluidly between hands-on analytical work and high-level executive communication.

• Experience influencing senior stakeholders across functions such as Product, Finance, Commercial, Marketing, Operations, Engineering, or Data.

• Strong commercial judgment, including understanding of metrics such as bookings, retention, NRR, funnel performance,LTV:CAC, and unit economics.

Preferred experience

• Experience across both B2C subscription and B2B SaaS environments.

• Experience in AI, transformation, operating model change, or measurement oforganisationaleffectiveness.

• Experience defining semantic logic, metric governance, or business logic in partnership with analytics engineering or data engineering teams.

• Experience contributing to board-level, leadership-level, or annual operating narratives.

• Python or similar analytical tooling for data exploration, prototyping, and scalable analysis.

Skills and capabilities

• Systemsthinking:able to connect local signals into a company-level point of view.

• Measurement design: strong instinct for defining the right metrics, thresholds, and operating cadences.

• Business storytelling: able to translate quantitative evidence into crisp recommendations for senior leaders.

• Stakeholder influence: can align senior partners without relying on formal authority.

• Bias for action:comfortablebuilding structure where little exists today.

• Strong judgment: able to separatesignalfrom noise and focus attention on what matters most.

• Curiosity about AI-first ways of working and how data science can shape the future operating model of a company.

Candidate profile

This role will suit a senior data scientist or analytics leader who enjoys working on ambiguous, high-leverage business problems. It is ideal for someone who likes building frameworks, connecting multiple sources of evidence, shaping decision systems, and operating close to senior leadership. It is less about shipping isolated models, and more about using data science and analytical thinking to make the wholeorganisationsmarter.

How we work

Decision Intelligence is a deliberately small, high-leverage team. We do not aim to be a reporting factory. We buildthe foundationsthat make decisions more trustworthy, more scalable, and more effective. We care about commercial impact, clarity of thinking, and pragmatic execution. You will have significant autonomy, broad exposure, and the opportunity to shape a capability that matters to the future ofBusuu

Chegg out our culture and benefits!

http://www.chegg.com/about/working-at-chegg/benefits/