Senior Applied AI & Data Scientist

REMOTE HAND
United States
12 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
2 years minimum
Compensation
$122,000.0 - $207,500.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Cloud Database Continuous Integration Relational Databases Python (Programming Language) PostgreSQL Machine Learning Tensorflow Standard Sql Search Technologies Software Deployment
+10 more
Pytorch Large Language Models Snowflake Generative AI Build Management Containerization Scikit Learn Xgboost Integration Frameworks Machine Learning Operations

Job description

The Senior Applied AI & Data Scientist is a senior individual contributor responsible for designing, building, and deploying AI-powered solutions that drive measurable business outcomes across life insurance, investments, membership, and charitable activities. This role integrates advanced analytics, machine learning, and generative AI within an enterprise-scale data and AI environment, collaborating with cross-functional teams to deliver explainable, production-ready capabilities under governance suited to regulated environments.

  1. Responsibilities:
  • Lead end-to-end delivery of AI solutions from problem framing through production deployment and measurement.

  • Design and implement LLM-enabled analytics and research capabilities using Retrieval Augmented Generation over enterprise data.

  • Develop agentic workflows and multi-step orchestration to automate business processes.

  • Build and deploy advanced statistical and machine learning models supporting various business domains.

  • Engineer reusable feature pipelines, embeddings, and semantic search strategies.

  • Define success criteria and evaluation plans including offline tests, human-in-the-loop review, and online measurement.

  • Collaborate with engineers to productionize models with CI/CD, monitoring, drift detection, and incident response.

  • Ensure consistent application of responsible AI practices including bias assessment, transparency, documentation, and audit controls.

  • Communicate insights and tradeoffs effectively to executives and technical teams.

  • Contribute to enterprise standards and patterns for MLOps and LLMOps.

Requirements

  • Strong Python and SQL skills; experience with ML libraries such as scikit-learn, XGBoost, PyTorch, or TensorFlow.

  • Experience with Snowflake and relational databases like PostgreSQL.

  • Knowledge of vector search, embeddings, and knowledge retrieval patterns.

  • Experience collaborating on production services including APIs, batch/stream pipelines, monitoring, and CI/CD.

  • Ability to define and execute robust model and LLM evaluation translating results into business KPIs.

  • Minimum 6 years in advanced analytics and machine learning with production deployment.

  • Minimum 2 years delivering GenAI/LLM solutions in an enterprise environment.

Preferred:

  • Experience in financial services, especially life insurance, annuities, or investments, with regulated model governance.

  • Familiarity with legacy-to-cloud data modernization and integration tools.

  • Experience with ML lifecycle tools, containerization, and API frameworks.

Benefits & conditions

  • The wage range for this role is approximately $122,000 to $207,500, subject to factors such as skills, experience, certifications, and location.

About the company

The organization is a tax-exempt Catholic fraternal benefit society providing financial security to members and their families through life insurance, long-term care insurance, disability income insurance, investment, and annuity products. Charity is central to its mission, donating substantial profits to support those in need and its faith. The organization also supports pro-life initiatives and aids Christians facing religious persecution, serving approximately two million members who volunteer within their communities.

Apply for this position

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