Senior Data Scientist

Customer.io · LATAM, Canada, USARemotosenior

En corto

▸Científico de datos senior que analiza comportamiento de usuarios en SaaS para mejorar producto y experiencia.
▸Diseña experimentos, construye modelos y comunica hallazgos para decisiones basadas en datos.
▸Destaca por su enfoque práctico, liderazgo sin autoridad y trabajo con equipos multidisciplinarios.

Proficiency in English is required for collaboration with global teams.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

¿Qué piden?

✓5+ años en ciencia de datos en entornos B2B SaaS o similares.
✓Fundamentos sólidos en estadística, experimentación y análisis de comportamiento.
✓Dominio de SQL y Python para análisis a gran escala.
✓Experiencia con plataformas de datos en la nube (Snowflake, BigQuery, etc.).
✓Habilidades de comunicación claras para stakeholders no técnicos.
✓Mentalidad de propiedad: define problemas y avanza sin requisitos perfectos.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

SQLPythonSnowflakeBigQuerydbtexperimentationbehavioral analyticsmachine learningAIdata modeling

¿A quién escribirle en Customer.io?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

About Customer.io Over 8,000 companies — from scrappy startups to global brands — use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data. io , and I'm looking for a Senior Data Scientist to help our teams make better decisions using customer and product data. You'll partner closely with Product, Marketing, and Customer Experience to evaluate product changes, design and analyze experiments, identify opportunities to improve the customer experience, and influence roadmap and business priorities. This is a hands-on role focused on analyzing behavior, building models, and turning data into clear, actionable direction. This role is ideal for someone who enjoys solving ambiguous problems, working closely with stakeholders, and applying data science pragmatically to support product and business decisions. We're looking for someone with an ownership mindset and a bias for action who balances technical rigor with practical decision-making. What we value Ownership: You take initiative and drive analytical work from concept to implementation. You don't wait for perfect requirements — you help define the problem and move the work forward. Curiosity: You naturally question assumptions and dig deeper into the "why" behind user behavior. You enjoy uncovering patterns in complex data and have the persistence to work through ambiguity and messy datasets. Analytical Rigor: You bring a thoughtful, structured approach to analytics and decision-making. You know how to define meaningful measures of success, evaluate changes with rigor, and distinguish signal from noise in complex behavioral data so teams can act with confidence. Communication: You can translate complex analytical concepts into clear recommendations for Product Managers, executives, and non-technical stakeholders. Collaboration: You work as a true cross-functional partner, balancing analytical rigor with practical business needs. You build trust by making data approachable, actionable, and reliable. What you'll do Analyze behavioral patterns across the customer lifecycle to identify trends, usage archetypes, and opportunities to improve adoption, engagement, and retention. Design experiments and measurement approaches to evaluate the impact of product and marketing changes - and help teams make decisions based on evidence rather than intuition. Build models and datasets that improve how teams segment customers, forecast outcomes, and identify trends. Apply machine learning and AI techniques where they solve practical problems, for both internal decision-making and customer-facing scenarios. Partner with Data Engineering to improve the quality, reliability, and accessibility of core data and metrics. Communicate findings clearly and directly so teams can make informed decisions without needing a statistics background. What we're looking for 5+ years of experience in a Data Science role within B2B SaaS or a similar product- or growth-focused environment. Strong foundation in statistics, experimentation, and behavioral analytics - with the ability to apply them pragmatically to real product and business problems. Proficiency in SQL and Python for large-scale analysis, modeling, and exploration. Experience with modern cloud data platforms (Snowflake, BigQuery, or similar); familiarity with dbt is a plus. Strong communication and stakeholder skills - you can explain complex analysis clearly to PMs, marketers, executives, and non-technical partners. An ownership mindset - you help define the problem and move work forward; you don't wait for perfect requirements.

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