Senior Data Scientist
hace 4 horas
Barcelona
ph3About seQura /h3 pseQura provides innovative, flexible and easy-to-use payment technologies that help merchants acquire, convert and retain more customers. /p pWe make a difference in sales performance by tailoring our solutions to different sectors, to address their unique pain points and deliver superior results in Retail, Education, Eyewear, Repairs and Travel. We also empower smart shopping to consumers who seek more value, convenience, and flexibility in their shopping, with new payment experiences that allow them to save, access interest‑free credit, or pay in small, comfortable instalments of up to 24 months. /p pBorn in Barcelona, seQura is a privately‑owned fintech, currently expanding throughout southern Europe and Latin America, growing above 50% CAGR and approaching 100 million in Annual Recurring Revenue. Over 5,000 businesses, almost 2 million shoppers, and almost 400 employees continue to rate us as one of the most loved and trusted fintechs out there, with an NPS of 87%, a Trustpilot rating of 4.7/5, and a Glassdoor rating of 4.7/5. /p h3About the role /h3 pWe are looking for a bSenior Data Scientist /b to help design, build, and evolve the intelligence behind seQura's Shopper App – a shopping app where users manage the payments they've made with seQura and discover and shop across merchants with rewards. /p pThis role focuses on building production‑grade machine learning systems that bring intelligence into real user flows. You will work on smart search, recommendations, and agent capabilities – models that understand context, reason over shopper needs, and help users discover and shop in ways that are relevant, personalized, and safe. /p pYou will collaborate closely with Product, Frontend, Data, and AI teams, playing a key role in shaping both the technical approach and the shopper experience. /p h3What challenges you'll be solving /h3 ul lipDesigning, building, and shipping the brecommendation systems /b that power the Shopper App, helping users discover relevant merchants, products, and offers across the full shopping lifecycle, while writing simple, clean, and efficient code. /p /li lipImproving bsmart search /b – relevance, ranking, intent detection, and query understanding – so shoppers quickly find what they're looking for. /p /li lipTurning ambiguous shopper needs and product ideas into reliable, scalable ML systems through a pragmatic, analytical, and accountable approach – favoring simplicity and iteration over premature complexity. /p /li lipOwning the full model lifecycle: sourcing and modeling data, feature engineering, training, evaluation, and deployment, with strong attention to detail and product ownership. /p /li lipDefining and tracking the bmetrics that matter /b (CTR, conversion, nDCG, MRR, zero‑result rate) and running experiments to measure real impact on shoppers. /p /li lipWorking closely with Product, Frontend, Data, and AI teams as a strong team player and communicator, driving alignment across disciplines. /p /li lipDriving change and efficiency by collaborating with partners and stakeholders from different disciplines, bringing motivation to learn, grow, and challenge the status quo. /p /li /ul h3About the Data team /h3 h3Team mission /h3 pTo build the intelligence behind seQura's Shopper App, creating personalized shopping experiences that help millions of users discover the right merchants, products, and offers at the right moment. /p pThrough machine learning, search, and AI, the team turns data into intelligent product capabilities that improve shopper engagement, increase conversion, and drive long‑term customer value. /p h3What we own /h3 ol liRecommendation systems, including collaborative filtering, content‑based, and hybrid approaches /li liSmart search capabilities, including relevance, ranking, intent detection, and query understanding /li liShopper recurrency and Lifetime Value (LTV) prediction models /li liAI‑powered product capabilities and intelligent agents /li liThe full machine learning lifecycle, from data exploration and feature engineering to model deployment and production monitoring /li liExperimentation frameworks and ML performance measurement /li /ol h3Team Structure /h3 pThe Data Science AI team works as an embedded product team alongside Software Engineering, Product, and Design. /p pData Scientists partner closely with Product Engineers to bring machine learning models into production, while collaborating with Data Platform to ensure scalable infrastructure and reliable ML workflows. /p h3How we work /h3 ol liProduct‑first mindset: every model is built to solve a real user problem and create measurable business impact. /li liEnd‑to‑end ownership across the entire machine learning lifecycle. /li liRapid experimentation through A/B testing, offline evaluation, and continuous iteration. /li liClose collaboration with Product, Engineering, and Design to integrate AI into the Shopper experience. /li liContinuous improvement driven by data, experimentation, and user behavior. /li /ol h3What to expect in the next 90 days /h3 h3Month 1 /h3 pYou’ll onboard with the Data Science team and gain a deep understanding of the Shopper App ecosystem, its architecture, existing machine learning systems, and data pipelines. Together with other Data Scientists and engineers, you’ll learn how search, recommendations, and shopper engagement models currently operate while getting familiar with the team’s ongoing initiatives. /p h3Month 2 /h3 pYou’ll take ownership of existing workstreams and begin contributing improvements to our smart search capabilities, including relevance and ranking. You’ll also collaborate closely with Product and Engineering to understand the current recommendation engine architecture and identify opportunities for future improvements. /p h3Month 3 /h3 pYou’ll deliver your first meaningful improvements to the Shopper experience, contributing to search quality or recommendation performance. You’ll help define and evaluate recommendation models, establish key success metrics such as CTR, conversion, nDCG, MRR, and zero‑result rate, and participate in experimentation through A/B testing to validate model impact. /p h3Tech stack environment /h3 pOur machine learning platform runs on AWS and is built on top of a modern data ecosystem that supports experimentation, production deployment, and continuous model improvement. /p pWe use Python as our primary development language, with ML workflows powered by SageMaker and orchestrated through Airflow. Our data platform relies on Redshift and S3 for storage and processing, while Kubernetes provides the infrastructure for scalable model serving and supporting services. /p pThe team works extensively with modern recommendation systems, information retrieval techniques, LLM‑powered applications, and experimentation frameworks. Models are continuously evaluated through offline metrics and online A/B testing to ensure measurable product impact. /p h3What you’ll need /h3 ul lib5+ years of experience as a Data Scientist / ML Engineer /b, with a strong track record of building and deploying models in production. /li libHands‑on experience with recommendation systems /b – collaborative filtering, content‑based, or hybrid approaches, including cold‑start and personalization. /li liExperience working on bproduct‑facing ML /b (search, ranking, personalization, or similar), where models directly shape user experience. /li liStrong bPython /b and bSQL /b; experience with the full ML lifecycle (data sourcing, feature engineering, training, evaluation, deployment, monitoring). /li liFamiliarity with bsearch and information retrieval /b (e.g. BM25, embeddings/KNN, OpenSearch/Elasticsearch) is a strong plus. /li liSolid grounding in clean coding, testing, and agile ways of working. /li libInitiative and ownership /b — you spot what needs doing and drive it forward, not afraid to use your voice, share your opinion, and challenge assumptions when something can be done better. /li libAdaptability /b — you’re comfortable with ambiguity and shifting priorities, and you learn fast in a fast‑moving environment. /li liEnglish proficiency. /li /ul h3What we offer /h3 pWe have a strong and sustainable foundation, where we provide a secure and reliable workplace. You have the freedom and trust to make the best contribution possible. /p pOne of our most valued strengths by our employees is our fellowship and supportive culture, which fosters a sense of belonging by working closely with our values. With us, you will have challenging projects to work on and push your skills and knowledge. /p pIn addition, we are very proud of the unique office we have, which offers a comfortable and inspiring environment to work in with everything you need. /p ul li23 vacation days + 2 days of free disposal per year. /li liFlexible compensation plan for transportation, restaurants, and kindergarten with Cobee. /li liHealth insurance discounts with Sanitas and DKV. /li liFlexible working hours. /li liA personal budget for professional development. /li liOffice workshops and meet‑ups to encourage community participation and career growth. /li liHybrid or remote work (up to 2 hours difference from GMT+2). /li /ul pMoreover, we have a bWellness Program /b that embraces a holistic approach by covering 6 areas (occupational, physical, financial, emotional, social, and environmental consciousness). Each area will include a variety of activities, and you’ll be able to choose from 34 different activities that best meet your needs to configure a plan that best works for you. /p h3Application process /h3 pWe kindly ask that you submit your CV in English, as it is the official language of our community. /p h3Equal Opportunity Statement /h3 pWe promote equal opportunity to all, regardless of age, color, gender identity, medical condition, physical or mental disability, race, religion, sexual orientation, or any other characteristic. We have an inclusive environment, and respect is above all. /p /p #J-18808-Ljbffr
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