Hybrid Senior Data Scientist

at PPLSI

• Job title: Senior Data Scientist
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Postgraduate Degree
• Tech skills: AWS, Azure, Cloud, Distributed Systems, Docker, Google Cloud Platform, Kubernetes, Microservices, Python
• Location requirements: Hybrid, United States

About the role

• Senior Data Scientist building predictive and generative models at LegalShield. Designing infrastructure for AI solutions with compliance and performance optimization in mind.

Responsibilities

• Develop predictive and generative ML models to support acquisition, retention, personalization, and member engagement.
• Fine-tune and adapt Large Language Models (LLMs) for LegalShield-specific use cases, including call transcript analysis, voice-of-customer workflows, and content generation.
• Conduct experimentation, model evaluation, and rigorous validation to ensure accuracy, fairness, and business alignment.
• Partner with business teams to design experiments, analyze results, and translate insights into actionable strategies.
• Build and maintain infrastructure for deploying and scaling ML/ GenAI models.
• Develop APIs, MCP servers and microservices to serve models across internal and external applications.
• Translate prototypes into production-grade systems for business and member-facing teams.
• Implement CI/CD pipelines, containerization, and orchestration (Docker, Kubernetes).
• Deploy and manage ML workflow orchestration, feature stores, and model registries.
• Monitor and optimize performance, drift, latency, and cloud costs.
• Ensure compliance with SOC2, HIPAA, GDPR, and other data privacy/security standards.
• Develop internal AI tools that improve productivity and deliver measurable cost savings.
• Develop external, member-facing AI-powered applications that create new value and enhance customer experience.
• Build reusable platforms and tools that accelerate AI/ML adoption across LegalShield.

Requirements

• Advanced degree in Data Science, Statistics, Computer Science, or a related field (or equivalent practical experience).
• 7+ years’ experience in software engineering, Machine Learning, or Applied Data Science (Python preferred; APIs, microservices, distributed systems).
• Proven ability to take AI/ML solutions from prototype to production and scale adoption across teams.
• Hands-on experience with Large Language Models (LLMs) and retrieval-augmented generation (RAG) pipelines, LLM Fine-tuning and training.
• Familiarity with ML infrastructure: feature stores, model registries, or workflow orchestration tools.
• Experience with CI/CD, Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
• Understanding of compliance and data privacy standards, and ability to apply them in AI systems.
• Proven track record of deploying and operating ML/AI systems in production.

Benefits

• Commitment to Equal Opportunity
• Equal Opportunity Employer