Data Scientist II

Data Scientist II, Commercial & Marketing AnalyticsWe are seeking a Data Scientist II to support our Digital Marketing and Commercial Analytics teams through advanced statistical modeling, predictive analytics, and customer insights. This individual will leverage customer, market, CRM, sales, and digital engagement data to identify growth opportunities, develop customer personas, forecast behaviors, and drive data-informed business decisions.This position goes beyond traditional reporting and dashboard development. The ideal candidate will have hands-on experience developing predictive models, applying machine learning techniques, and translating large, complex datasets into actionable strategies that improve commercial and marketing outcomes.Candidates with experience in Life Sciences, Biotechnology, Medical Device, Healthcare, or other regulated industries are strongly preferred.Key ResponsibilitiesDevelop predictive models to identify customer behaviors, engagement patterns, buying propensities, and market opportunities.Build customer segmentation frameworks and target personas using commercial, market, CRM, and digital marketing data.Apply statistical modeling and machine learning techniques to support forecasting, targeting, and business planning initiatives.Analyze marketing and sales performance across the customer lifecycle, including lead generation, customer acquisition, engagement, conversion, and retention.Design and evaluate experiments, A/B tests, and observational analyses to measure campaign effectiveness and inform strategic decisions.Identify trends, anomalies, performance gaps, and growth opportunities across customer segments, products, campaigns, and geographies.Partner with Marketing, Commercial Operations, Sales Leadership, and Digital teams to translate analytical findings into actionable recommendations.Build visualizations and executive-level reporting to communicate complex analytical concepts to technical and non-technical stakeholders.Evaluate and integrate internal and external data sources to improve customer targeting strategies and market intelligence.Develop, maintain, and optimize analytical models while ensuring data quality, accuracy, and scalability.Required QualificationsWhile this position is remote, candidate must be located in California.Bachelor's degree in Statistics, Mathematics, Economics, Econometrics, Data Science, Applied Mathematics, Computer Science, or a related quantitative discipline.3+ years of experience in Data Science, Predictive Analytics, Marketing Science, Commercial Analytics, or a related field.Experience developing predictive models and applying statistical methodologies to solve business problems.Strong understanding of:Customer segmentationBehavioral analyticsForecastingMachine learningStatistical inferenceExperience working with large structured and unstructured datasets.Proficiency in one or more of the following:PythonSQLRSASExperience with data visualization tools such as Power BI, Tableau, or similar platforms.Knowledge of CRM and marketing platforms such as:SalesforceHubSpotEloquaAdobe AnalyticsAbility to communicate complex analytical findings to both technical and business audiences.Strong problem-solving skills with the ability to connect data insights to business outcomes.Preferred QualificationsMaster's degree in Statistics, Economics, Econometrics, Mathematics, Data Science, Machine Learning, or a related quantitative field.Experience within:Life SciencesBiotechnologyPharmaceuticalMedical DeviceHealthcare industriesExperience supporting commercial analytics, marketing analytics, customer insights, market research, or go-to-market teams.Experience developing:Customer personasPropensity modelsSegmentation strategiesDemand forecasting modelsHistory in experimental design, causal inference, or advanced statistical modeling techniques.Experience working within cross-functional global organizations.What Success Looks LikeThe successful candidate will combine quantitative rigor with business curiosity. They will use statistical thinking, predictive modeling, and machine learning techniques to understand customer behavior, anticipate future trends, and help drive commercial growth.Rather than simply reporting what happened, this individual will help the business understand what is likely to happen next and why, enabling more effective commercial and marketing decisions through data-driven insights.