What you’ll be doing

— Hire, scale, and nurture a Monetization Product Analytics team. Define a long-term vision and set them up for success. Keep them motivated by fostering an environment where ambitious goals lead to meaningful wins.

— Inform & shape the strategy of Preply’s subscription model, payments operations, and learners scheduling experience as well as how tutors set their availability.

— Master the dynamics of tutors/learners interaction across multiple stages of the user journey (booking, subscription management, payments, etc.).

— Champion strategic projects that will change how we use data, and how we understand our users and business. Promote data literacy and self-service analytics across the organization.

— Enable accurate impact measurement for our product initiatives and an optimal prioritizing of the product roadmap.

— Work closely with our Data & analytics engineer team to define standard methodology, tools and best practices for your team.

— Participate in the definition of tracking events, engagement metrics and key performance indicators.

What you need to succeed

— 3+ years of proven experience leading and managing Analytics and Data Science teams, with a strong track record of coaching, mentoring, and developing talent, complemented by 4 years of hands-on experience as an individual contributor in analytics.

— Demonstrated ability to set high standards, raise the technical bar, and instill a culture of accountability, curiosity, and continuous learning.

— Experienced in defining team strategy, setting priorities, and aligning analytics goals with company-wide business objectives.

— Experience with experimentation platforms, tracking definition as well as AB test design and evaluation.

— Hands-on experience with advanced analytics techniques (e.g., causal inference, predictive modeling, attribution methods) and solid grounding in SQL, Python/R, and BI platforms (such as Amplitude, Looker, Snowflake, Data Bricks or similar).

— Proven ability to lead change management, embedding experimentation and analytics into product culture with a creative mindset and proactive attitude toward hypothesis generation, rapid testing, and iteration.

— A passion for driving insights and curiosity on user behavior and business metrics. Creative mindset and proactive attitude towards the creation and evaluation of new hypotheses.

Nice to have

— Previous experience in Marketplaces and/or digital businesses (B2B, B2C, B2B2C).

— Previous experience in a subscription based business or in a payments team.

— Foundational domain knowledge of Gen-AI and Machine Learning to be able to assist PMs and squads as they design and deliver AI-Driven features.

Why you’ll love it at Preply

— An open, collaborative, dynamic and diverse culture;

— A generous monthly allowance for lessons on Preply.com, Learning & Development budget and time off for your self-development;

— A competitive financial package with equity, leave allowance and health insurance;

— Not in Barcelona? We offer an attractive relocation package to join us in our Preply Barcelona Hub;

— Access to free mental health support platforms;

— Access to Gympass-partnered wellness and gym centers throughout Spain to promote and support well-being and physical health;

— The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting!).

Team description

The Data team drives Preply to make the best decisions for our business, learners and tutors, by building a data-driven organization and the best data products. As Data Managers, we are deeply involved in people, business, products, marketing, and technologies. In partnership with product managers, we look for business opportunities and take them to bring the company to the next level. All Product Analytics team members embedded in cross-functional squads (approximately 3 - 6) will report to this position.

‍

Tech stack

Hands-on experience with advanced analytics techniques (e.g., causal inference, predictive modeling, attribution methods) and solid grounding in SQL, Python/R, and BI platforms (such as Amplitude, Looker, Snowflake, Data Bricks or similar).