Internship focused on building predictive models, optimization solutions, and AI-powered tools to improve a nationwide moving and storage operation.
Compensation
$25.00-$30.00/hour
Responsibilities
Own a focus project
Build and validate predictive models
Formulate and solve routing, scheduling or capacity optimization
Build AI agents that automate manual workflows
Prepare and validate operational data
Requirements
Bachelor's or Master's degree in a quantitative or technical field such as Data Science, Business Analytics, Statistics, Operations Research, Computer Science, Artificial Intelligence, Applied Mathematics, Industrial Engineering, Economics
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 for marketing analytics across FMCG, BFSI, retail, and automotive clients.
Responsibilities
Build and maintain lead scoring models
Develop churn prediction models
Design and execute Media Mix Modeling studies
Write efficient SQL queries
Build and productionize data pipelines and models in Python
Requirements
Bachelor's/Master's degree in Statistics, Computer Science, Data Science, Economics, or a related quantitative field
Develop and maintain analytical workflows, data systems, and AI-enabled tooling for process monitoring, predictive modeling, and anomaly detection in cell therapy and biologics manufacturing.
Compensation
The annual base pay (or hourly rate of compensation) for this position ranges from $101,643.20 - $152,464.80. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles.
Responsibilities
Develop and maintain analytical workflows for multivariate process monitoring
Build and maintain data systems and analytical platforms
Support development of hybrid mechanistic and data-driven models
Translate statistical findings into actionable insights
Collaborate cross-functionally with R&D, MSAT, Manufacturing Operations, Quality, and IT
Requirements
Ph.D. in Chemical Engineering, Biochemical Engineering, Biotechnology, Data Science, Statistics, or related field
M.S. in Chemical Engineering, Biochemical Engineering, Biotechnology, Data Science, Statistics, or related field
B.S. in Chemical Engineering, Biochemical Engineering, Biotechnology, Data Science, Statistics, or related field
Nice to have: Cloud data systems (AWS, Snowflake, Databricks)
Nice to have: Interactive analytical applications (Streamlit, Dash)
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.
Partner with business stakeholders to frame problems, define success metrics, and translate business needs into analytical and data science solutions.
Perform exploratory data analysis, statistical analysis, hypothesis testing, and experimentation to identify patterns, drivers, and opportunities.
Design, develop, evaluate, and refine machine learning and statistical models for use cases such as forecasting, classification, segmentation, and anomaly detection.
Apply appropriate validation methods; assess model performance and limitations; and communicate uncertainty, assumptions, and trade-offs.
Prepare, transform, and integrate structured, semi-structured, and unstructured data. Develop reusable features and analytical datasets using Python and SQL.
Requirements
Bachelor’s or master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
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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