Scientist, Senior

The Senior Data Scientist (Strategy Data Science) is a senior individual contributor on Infor's Post-Sales Data Science team. This role is responsible for owning analytical workstreams end to end in close partnership with business stakeholders across various business functions. You will work on high-priority questions related to customer adoption, retention, expansion, and growth, translating strategic business problems into rigorous, actionable analysis. This is a role for someone who combines strong analytical and technical skills with the communication ability and business judgment to create measurable business impact with data-driven insights. A Typical Day in the Life Includes: Own data science workstreams end to end. Take business questions from initial scoping through data analysis, insight synthesis, and stakeholder communication. Manage day-to-day relationships with business partners. Develop exploratory insights, statistical models, and causal frameworks as appropriate. Frame problems before solving them. Work with stakeholders to translate business objectives into clear analytical frameworks. Influence problem framing to ensure questions can be answered using data science. Translate findings into decisions. Develop clear narratives and exec-facing presentations that connect analytical results to business decisions. Prioritize actionability and connection to business outcomes without sacrificing methodological transparency. Collaborate across team on data foundation and DS practices. Work as part of a cohesive data science pod to share best practices, innovations and business/data knowledge. Support turning insights into actions. Develop production-ready analytical scripts and contribute to collaborations with IT on deployment of insights into operational workflows. Basic Qualifications: SaaS product or customer analytics background. Significant experience working on user/customer adoption, retention, engagement, or lifecycle analytics in a B2B SaaS or enterprise software environment. Comfort thinking in terms of cohorts, funnels, and behavioral metrics. End-to-end analytical ownership. Demonstrated ability to independently own a full analytical project, from problem framing to data acquisition and preparation, analysis, and insight communication, all with minimal technical supervision. Strong SQL and Python skills. Ability to independently explore and transform data, build analytical datasets, and implement statistical models. Comfort working in Snowflake. Stakeholder-facing communication. Proven ability to present analytical findings to business stakeholders in a clear, compelling, and understandable way. Experience relating methodology to business narrative and clearly identifying recommended actions. Statistical rigor. Solid grounding in statistical methods relevant to business analytics: regression modeling, segmentation, A/B testing, survival analysis, propensity modeling. Ability to explain methodological choices clearly and evaluate and articulate tradeoffs between approaches. Full professional proficiency in English. Ability and willingness to work on-site three days per week as part of a hybrid work model. Legal authorization to work permanently in Mexico for any employer without requiring a visa transfer or visa sponsorship now or in the future. Preferred Qualifications: Customer Success domain experience. Prior work supporting or embedded within a Customer Success organization, or direct experience with adoption, churn, and expansion analytics. Experience influencing business decisions with data. Examples of analytical work that demonstrably changed a business decision or drove a stakeholder to action that measurably impacted KPIs. Data visualization and storytelling. Strong demonstrated instinct for visual communication of quantitative findings. Experience with AI data science workflows. Comfort with using generative AI tools to accelerate data science workflows. Location: Montes Urales Norte 505, Lomas de Chapultepec, Miguel Hidalgo, 11000 Ciudad de México