• Develop and evolve statistical and causal inference methodologies that strengthen the rigor and reliability of Northbeam’s marketing measurement products • Enhance the accuracy, robustness, and scalability of existing MMM pipelines • Write production-quality Python and SQL, collaborating closely with Engineering to integrate statistical workflows into scalable systems • Rigorously assess model assumptions, identify potential sources of bias, and implement mitigation strategies • Debug data and modeling issues in production and improve the reliability of customer-facing results • Translate complex statistical reasoning into clear, decision-ready insights for internal stakeholders and customers

• Own the analytical strategy for a product area: identifying the highest-leverage questions, defining the measurement framework, and ensuring data-driven decisions • Serve as a strategic partner to product and engineering leadership, translating ambiguous business problems into analytical approaches and clear, actionable recommendations • Define north-star metrics and measurement strategies to set goals, evaluate progress, and make trade-offs • Design and oversee experiments and causal analyses, ensuring methodological rigor and that results drive real product decisions • Develop and maintain a deep understanding of user growth dynamics: how acquisition, activation, and retention interact to drive growth, and use that understanding to diagnose metric movements, explain trends to leadership, and anticipate emerging risks or opportunities • Contribute and own areas of the team’s forecasting and growth modeling efforts, helping translate statistical models into actionable growth strategies • Mentor and elevate other data scientists through code review, methodology guidance, and establishing reusable analytical frameworks • Represent data science in cross-functional forums, making the case for what the data shows even when it challenges prevailing assumptions • Drive alignment across data science, data engineering, and product on shared priorities like data quality, metric definitions, and instrumentation

• Collect, analyze, and interpret large datasets to extract valuable insights • Develop and implement statistical models and algorithms • Perform exploratory data analysis to identify patterns • Build and maintain data pipelines • Develop data visualizations and reports • Collaborate with multidisciplinary teams • Evaluate and select appropriate tools and technologies • Stay up to date with the latest trends

Role Description We are looking for a Data Science Manager to lead advanced analytics initiatives within a large retail environment. This role is highly technical and focused on digital/product analytics and predictive modeling to identify friction points across the customer journey. The position also requires strong strategic involvement, collaborating closely with stakeholders to define priorities, influence roadmaps, and drive data-informed decision-making. - Lead the design and implementation of predictive models to optimize customer journey and digital product performance - Analyze large-scale datasets to identify user behavior patterns, friction points, and growth opportunities - Partner with product, marketing, and business stakeholders to define data-driven strategies and priorities - Translate business problems into analytical frameworks and actionable insights - Drive roadmap prioritization based on data insights and business impact - Mentor and guide data scientists, fostering best practices in modeling and analytics - Communicate complex analytical findings to non-technical stakeholders in a clear and impactful way - Collaborate with data engineering teams to ensure data availability and quality - Continuously improve experimentation frameworks (A/B testing) and measurement methodologies Qualifications - Strong experience in Data Science, with a focus on product analytics or digital analytics - Proven experience building and deploying predictive models (e.g., churn, propensity, recommendation systems) - Advanced proficiency in Python or R for data analysis and modeling - Solid knowledge of SQL and working with large datasets - Experience with experimentation frameworks (A/B testing) - Strong business acumen and ability to connect data insights with business outcomes - Experience working with cross-functional teams and stakeholders - Leadership or mentoring experience in data teams - Excellent communication and storytelling skills Requirements - Advanced English level required (written and spoken) Benefits - 📚 Learning Opportunities: - Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. - Access to AI learning paths to stay up to date with the latest technologies. - Study plans, courses, and additional certifications tailored to your role. - Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. - English lessons to support your professional communication. - 👩‍🏫 Mentoring and Development: - Career development plans and mentorship programs to help shape your path. - 🎁 Celebrations & Support: - Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. - Company-provided equipment. - ⚖️ Flexible working options to help you strike the right balance. - Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.