Senior Data Scientist especializado en experimentación y medición de impacto causal, liderando el diseño, ejecución y análisis de experimentos A/B y métodos cuasi-experimentales para impulsar decisiones de negocio.
Responsibilities
Diseñar y medir el impacto de iniciativas basadas en evidencia causal sólida
Liderar el diseño y la medición de experimentos A/B de principio a fin
Definir métricas y metodologías de medición
Analizar resultados y defender conclusiones ante stakeholders
Implementar modelos de ML en producción y medir su impacto incremental
Data Scientist to build and maintain predictive models and media mix modeling studies for marketing and media analytics across FMCG, BFSI, retail, and automotive clients.
Responsibilities
Build and maintain lead scoring models to prioritize high-intent customers/prospects for sales and marketing teams
Develop churn prediction models to identify at-risk customers and support retention strategies
Design and execute Media Mix Modeling (MMM) studies to measure channel-level marketing effectiveness and guide budget allocation
Write efficient SQL queries to extract, transform, and validate data from large marketing and transactional datasets
Build and productionize data pipelines and models in Python (pandas, scikit-learn, statsmodels, or equivalent)
Requirements
Bachelor's/Master's degree in Statistics, Computer Science, Data Science, Economics, or a related quantitative field
Develop and maintain analytical workflows for multivariate process monitoring, predictive modeling of batch outcomes, and anomaly detection on high-dimensional process data for cell therapy development.
Compensation
The annual base pay (or hourly rate of compensation) for this position ranges from $101,643.20 - $152,464.80.
Responsibilities
Develop and maintain analytical workflows for multivariate process monitoring
Predictive modeling of batch outcomes from incoming material
Anomaly detection on high-dimensional process data
Build and maintain data systems, analytical platforms, and AI-enabled tooling
Support development of hybrid mechanistic and data-driven models
The Senior Power BI & Data Analyst transforms complex commercial, operational and financial data into actionable insights that support strategic decisions, revenue growth, profitability and operational efficiency.
Responsibilities
Design and maintain enterprise Power BI dashboards, reports and semantic models.
Build advanced DAX measures, Power Query transformations and dimensional models.
Integrate ERP, CRM, finance and supply chain data; implement row-level security and refresh monitoring.
Lead development and deployment of homeowners insurance pricing and risk models, including GLM and machine learning approaches, while mentoring junior data scientists and collaborating with actuarial, product, and engineering teams.
Compensation
Pay Range:* $138,800 - $194,300 annually
Responsibilities
Contribute to modeling standards and best practices for insurance pricing and risk modeling
Support and mentor junior data scientists through code review, knowledge sharing, and technical guidance
Build, validate, and deploy GLM-based models for homeowners insurance pricing
Build machine learning models (GBMs, neural networks, etc.) that drive underwriting accuracy, competitive positioning, and profitability
Develop ensemble models predicting insured-level profitability, customer retention, and conversion
Requirements
Master’s or PhD in Statistics, Mathematics, Computer Science, or a related quantitative field
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