Top Hybrid Data Science Jobs

Senior analytics partner for consumer product experiences focused on visual content and media quality. Own experimentation, business analytics, and measurement; design multivariate tests; define success metrics; build self-service AI-enabled reporting; improve data quality and ETL pipelines; and translate analyses into product recommendations that drive engagement and lead generation.

The Senior Associate - Data Scientist will develop AI and machine learning solutions, focusing on model lifecycle management and delivering AI initiatives in collaboration with business teams.

The Senior Data Scientist will design and implement AI-enabled products using clinical trial data, mentor team members, and collaborate with stakeholders.

Lead data-science work for matching features: translate product goals into data problems, design and analyze A/B tests, perform exploratory analysis and data mining, generate strategic insights, and collaborate with AI, product, design, and engineering to develop and iterate production ML models.

Validate and test credit risk models, prepare validation reports and documentation, support model releases and monitoring, automate model training, perform ad-hoc statistical analyses, and communicate findings to stakeholders to support risk management and production deployment.

The Applied Scientist role involves developing quantitative models for decision-making under uncertainty, focusing on pricing, demand modeling, and risk management. Responsibilities include building and optimizing models, collaborating with engineering and product teams, and translating complex problems into actionable solutions.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.

Lead and coach a data science team to design, develop, and deploy predictive and prescriptive analytics for business impact. Partner with senior leaders to identify opportunities, drive adoption of models, manage vendors, and establish data science methodology and best practices.

The Senior Data Scientist will engage with business partners to solve problems using data science, lead model development, and mentor others, focusing on supply chain and causal modeling.

Lead measurement and decision systems for patient growth: own incrementality, design experiments, build LTV/retention/forecasting models, create trusted marketing metrics, partner with Engineering for measurement plumbing, diagnose performance shifts, influence channel allocation, and mentor growth analytics teams.