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 HR@AmeriLife.com. 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. About Us Since 1971, AmeriLife has served the needs of its clients. Today, we are a national leader in the development, marketing and distribution of annuity, life and health insurance solutions, with more than 1,000 associates across the country. AmeriLife partners with leading carriers to support consumers' financial-wellness goals. Our Mission AmeriLife offers insurance and retirement solutions to provide peace of mind and help people live longer, healthier lives. Our Values AmeriLife practices five core values at all levels of the organization: Honesty

• We deal truthfully with all of our clients Integrity
• We always do what is right for our clients Accountability
• We put our clients' needs first by taking take ownership of our actions Excellence
• We do more than our jobs by going the extra mile for our clients Courage
• We stand up for what is right