Principal Data Scientist
J
JobgetherData science and AI
Based in the United StatesFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- At least 8 years of experience in data science, machine learning, or applied science, or 6+ years with a PhD
- Required Skills
- PythonSQLMachine LearningPyTorchTensorflowA/B testingGenerative AI
Requirements
- Hold a bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline; a master’s degree or PhD in a quantitative field is strongly preferred.
- Have at least 8 years of experience in data science, machine learning, or applied science, or 6+ years with a PhD.
- Demonstrate a track record of delivering production-quality models with measurable business outcomes.
- Have experience setting technical direction across AI/ML solutions and influencing strategic decisions by senior business leaders.
- Bring experience developing personalization, recommendation, decision-optimization, or marketing-science solutions.
- Have practical expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods.
- Have hands-on experience with generative AI and AI-assisted development tools, such as LLM APIs, AI coding assistants, and agent frameworks.
- Demonstrate expert proficiency in Python and SQL, and experience with PyTorch or TensorFlow and distributed data processing technologies.
- Have experience deploying and operating AI/ML solutions in cloud environments, including production monitoring, maintenance, and lifecycle management.
- Demonstrate scientific and engineering discipline in reproducibility, model evaluation, production readiness, and enterprise integration.
- Preferred: Experience in commercial analytics in pharmaceutical, biotechnology, healthcare, or life sciences, or with prescription, claims, and engagement data sources.
- Preferred: Experience with omnichannel analytics, customer journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action solutions.
Responsibilities
- Define the multi-year data science vision and technical roadmap for omnichannel engagement analytics.
- Identify and prioritize AI and analytics opportunities, develop business cases, and influence investment decisions.
- Build and prototype generative AI solutions using LLM APIs, AI-assisted development tools, agentic frameworks, RAG, and context engineering.
- Develop predictive, causal, recommendation, next-best-action, and sequential decision models using complex, multi-source datasets.
- Establish evaluation frameworks and measurement strategies, including A/B testing and quasi-experimental methods.
- Partner with product owners to define business problems, outcomes, success metrics, and scalable technical solutions.
- Collaborate with engineering and technology teams to deploy, monitor, maintain, and manage production AI/ML solutions.
- Establish best practices for model development, code quality, reproducibility, peer review, scientific validation, and responsible AI.
- Mentor data scientists and lead technical workstreams involving external analytics vendors and partners.
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