Data Scientist

Our Company

Explore how you can contribute at AmeriLife.

For over 50 years, AmeriLife has been a leader in the development, marketing and distribution of annuity, life and health insurance solutions for those planning for and living in retirement.

Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry.

Job Summary

AmeriLife is a national leader in insurance and financial services. Our AI & Data Science team is small, high-impact, and building a modern AI capability from the ground up on Databricks. You’ll ship production solutions — from predictive forecasting to AI agents — that directly transform how the business operates across our Health and Wealth verticals.

Job Description

Why This Role Stands Out

• Databricks-first platform — Lakehouse architecture with Unity Catalog, MLflow, and scalable compute
• Real AI work — design and deploy AI agents, RAG systems, and LLM-powered solutions in production
• End-to-end ownership — from problem framing through deployment and monitoring
• Direct business impact — work with business leaders on high-visibility initiatives
• Shape the future — influence technical direction, tooling, and best practices on a growing team

What You’ll Do

As a Data Scientist on our AI & Data Science team, you will partner with engineering, analytics, and business stakeholders to translate complex problems into scalable, production-ready solutions. Your work will span the full lifecycle — from exploratory analysis through model deployment and ongoing optimization.

Day-to-day, you will design and build predictive models for forecasting and optimization, develop intelligent automation using AI agents and large language models, engineer features and pipelines on the Databricks Lakehouse platform, and evaluate and iterate on both traditional ML and generative AI solutions to ensure they deliver reliable business value.

This role is ideal for someone who thrives at the intersection of rigorous statistical thinking, practical data engineering, and applied AI innovation — and who wants to do that work on a modern platform where their contributions are visible and valued.

Technical Requirements

Statistics & Machine Learning

Required

• Strong foundation in statistical modeling and ML, with experience selecting appropriate approaches for different business problems
• Proven experience building and validating time-series forecasting models in production environments
• Hands-on expertise with ensemble/boosting algorithms (XGBoost, LightGBM) for structured data
• Experience with A/B testing design, hypothesis testing, and rigorous model evaluation techniques
• Comfort working with imperfect, real-world datasets — handling missing data, class imbalance, and feature drift

Preferred

• Unsupervised learning (clustering, anomaly detection), hierarchical/probabilistic forecasting, Bayesian methods, or causal inference
• Experience optimizing models for business ROI; exposure to reinforcement learning or advanced optimization

Databricks Platform & Data Engineering

Required

• Strong Python proficiency for data analysis, modeling, and production development
• Experience with Databricks notebooks, clusters, and workflows for data science and ML
• Working knowledge of PySpark for large-scale data processing and feature engineering
• Advanced SQL skills across Lakehouse architectures; experience with MLflow for experiment tracking and model registry
• Clean, testable code practices with Git-based version control (e.g., Databricks Repos, GitHub)

Preferred

• Unity Catalog, Delta Lake/Delta Live Tables, medallion architecture patterns
• Databricks Feature Store, Model Serving, Workflows orchestration, or data quality frameworks
• Experience designing APIs for model serving; CI/CD for ML workflows
• Databricks Accreditations: Fundamentals 

Cloud & Infrastructure

Required

• Hands-on cloud platform experience (Azure preferred; AWS/GCP also valued) with Docker containerization
• Understanding of cloud-native data architectures, distributed processing, and data governance/RBAC

Preferred

• Azure ecosystem experience (Data Factory, Azure AI Services, Azure OpenAI); MLOps practices and model monitoring
• Certification: Azure Fundamentals or AWS Cloud Practicioner

Applied AI & Intelligent Automation

Required

• Hands-on prompt engineering and LLM integration for production use cases
• Experience building or orchestrating AI agents and multi-step workflows (LangChain, LangGraph, or similar)
• Ability to evaluate AI outputs systematically and implement guardrails for reliability and safety
• Strong judgment on when to apply traditional ML vs. generative AI and the trade-offs involved

Preferred

• Enterprise LLM experience (fine-tuning, evaluation, deployment); RAG architectures with vector databases and semantic search
• NLP/text analytics; transformer architectures; Databricks Mosaic AI or Foundation Model APIs
• Structured AI evaluation methods (offline/online testing, human-in-the-loop); computer vision exposure

Experience & Business Impact

Required

• 3+ years in data science, machine learning, or applied AI roles
• Proven ability to communicate complex results as clear, actionable insights for technical and non-technical audiences
• Full production ownership experience — from problem definition through deployment, monitoring, and iteration
• Experience leading team-level projects with planning, execution, and delivery accountability

Preferred

• Insurance, financial services, healthcare, or regulated industry experience
• Track record of influencing technical direction and elevating team practices

Our Tech Stack

• Data Platform: Databricks (Lakehouse, Unity Catalog, Delta Lake, MLflow, Workflows)
• Languages: Python, SQL, PySpark
• AI/ML: LangChain, LangGraph, Azure OpenAI, Hugging Face, scikit-learn, XGBoost
• Cloud: Microsoft Azure (Data Factory, AI Services, DevOps)
• Dev Tools: Git, Docker, VS Code / Cursor IDE, CI/CD pipelines

Education & Location

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative field. Equivalent experience with a strong portfolio also considered.
• U.S.-based; remote-friendly with potential hybrid arrangements depending on business needs

Compensation

• Salary Range: $125,000 to $135,000

• Salary offers will vary commensurate with experience, education, skills, and training 

What AmeriLife Offers

A comprehensive benefits package that includes PTO, medical, dental, vision, retirement savings, disability insurance, and life insurance.

Equal Employment Opportunity Statement

We are an Equal Opportunity Employer and value diversity at all levels of the organization. All employment decisions are made without regard to race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity or expression, age, national origin, ancestry, disability, genetic information, marital status, veteran or military status, or any other protected characteristic under applicable federal, state, or local law. We are committed to providing an inclusive, equitable, and respectful workplace where all employees can thrive.

Americans with Disabilities Act (ADA) Statement

We are committed to full compliance with the Americans with Disabilities Act (ADA) and all applicable state and local disability laws. Reasonable accommodations are available to qualified applicants and employees with disabilities throughout the application and employment process. Requests for accommodation will be handled confidentially. If you require assistance or accommodation during the application process, please contact us at [email protected].

Pay Transparency Statement

We are committed to pay transparency and equity, in accordance with applicable federal, state, and local laws. Compensation for this role will be determined based on skills, qualifications, experience, and market factors. Where required by law, the pay range for this position will be disclosed in the job posting or provided upon request. Additional compensation information, such as benefits, bonuses, and commissions, will be provided as required by law. We do not discriminate or retaliate against employees or applicants for inquiring about, discussing, or disclosing their pay or the pay of another employee or applicant, as protected under applicable law. Pay ranges are available upon request.

Background Screening Statement

Employment offers are contingent upon the successful completion of a background screening, which may include employment verification, education verification, criminal history check, and other job-related inquiries, as permitted by law. All screenings are conducted in accordance with applicable federal, state, and local laws, and information collected will be kept confidential. If any adverse decision is made based on the results, applicants will be notified and given an opportunity to respond.