[Remote] Data Scientist II

Note: The job is a remote job and is open to candidates in USA. Radian Group is a trusted, global multi-line specialty insurer that helps businesses navigate risk with confidence. The Data Scientist II role involves developing data science products, including computer vision systems and valuation models, while working collaboratively in a hands-on capacity to drive projects forward.

Responsibilities

• Analyze data to support (or disprove) a thesis – You'll dig into data, form hypotheses, and let evidence guide your conclusions. We value intellectual honesty over confirmation bias
• Select and implement the right tools for the job – Not every problem needs a transformer. Some problems just need a well-tuned gradient boosting model. You'll know the difference
• Build, train, test, and validate models – From algorithm selection to hyperparameter tuning to rigorous evaluation. You'll need solid grounding in math and statistics to evaluate model performance and defend your choices
• Engineer models into production – This isn't research for research's sake. Your models need to run reliably in the real world, on real infrastructure, serving real customers
• Document your work – Future you (and your teammates) will thank you. We maintain clear documentation for models, testing protocols, and decision rationale
• Monitor and improve models in production – Models drift. Data changes. You'll keep watch and know when it's time to retrain, rebuild, or rethink
• Explore agentic and reasoning systems – We're investing in semi-autonomous systems that can plan and act. You'll help us figure out what's hype and what's actually useful
• Perform other duties as assigned or apparent

Skills

• 2-5+ years of hands-on AI experience including working with LLMs (GPT, Claude, Qwen, or similar) via API/SDK and building and deploying ML or DL models in production environments
• Core to success in this role is the ability to evaluate model performance beyond surface metrics and explain uncertainty clearly. This requires a strong scientific foundation in linear algebra, calculus, probability, and statistical inference
• Understanding of prompt engineering, RAG architectures, fine-tuning approaches, and embedding models
• Strong command of supervised and unsupervised learning techniques: regression, classification, clustering, dimensionality reduction, ensemble methods
• Ability to evaluate LLM outputs critically and design appropriate guardrail systems
• Familiarity with tokenization, context windows, and inference optimization
• Deep learning expertise including CNNs, RNNs/LSTMs, transformers, and attention mechanisms
• Practical experience implementing Reinforcement Learning algorithms: Q-learning, policy gradients, actor-critic methods, or multi-armed bandits
• Understanding of reward shaping, exploration vs. exploitation tradeoffs, and temporal difference learning
• Ability to evaluate and define the appropriate model for each problem based on business requirements
• Experience with model testing frameworks, model evaluation, validation strategies, and model documentation
• Strong Snowflake/SQL skills and experience working with large datasets
• Proficiency with pandas, NumPy, and data manipulation at scale
• Experience with data quality assessment, cleaning, and validation
• Proficiency writing clean, maintainable, production-quality Python code
• Familiarity with ML pipelines, feature engineering, and data preprocessing at scale
• Understanding of model serving patterns: batch inference, real-time APIs, streaming
• Experience deploying to production and maintaining models over time
• Working experience with AWS services: Bedrock, SageMaker, Lambda, S3, EC2, Step Functions, CloudWatch, EKS
• Familiarity with containerization (Docker) and orchestration basics
• Experience with infrastructure-as-code using CDK or terraform
• Git version control and collaborative development practices
• Altassian suite of JIRA and Confluence, Slack for communications
• Jupyter notebooks for exploration, Python packages for production
• PyTorch and/or TensorFlow
• Scikit-learn, XGBoost, LightGBM, autogluon, Catboost
• MLflow, Weights & Biases, or similar experiment tracking
• Experience building autonomous or semi-autonomous AI systems
• Familiarity with agent frameworks (Strands, AgentCore, LangChain), platforms, tool use patterns, or multi-step reasoning architectures (ReAct, chain-of-thought, MCP)
• Understanding of planning algorithms, state management, and decision-making under uncertainty
• Experience with image classification, object detection, or segmentation
• Familiarity with transfer learning and pretrained vision models
• Understanding of image preprocessing, augmentation, and feature extraction
• Background in real estate, mortgage, financial services, or logistics
• Experience with valuation models, risk scoring, or pricing algorithms
• Familiarity with time series forecasting or geospatial analysis
• CI/CD pipelines for ML workflows
• Model versioning, A/B testing frameworks, and canary deployments
• Monitoring, alerting, and drift detection in production
• Experience with model documentation and governance requirements

Benefits

• Anticipated base salary from $98,000 to $148,000 based on skills and experience
• This position is eligible to participate in an annual incentive program.
• This role is eligible for 25 days of paid time off annually, which is prorated in the year of hire based on hire date.
• Based on your hire date, you will be eligible for 9 paid holidays + 2 floating holidays.
• Parental leave is also offered as an opportunity for all new parents to embrace this exciting change in their lives.
• Multiple medical plan choices, including HSA and FSA options, dental, vision, and basic life insurance.
• 401(k) with a top of market company match (*did we mention the company match is immediately vested?!)
• An opportunity to participate in Radian’s Employee Stock Purchase Plan (ESPP).
• Our Homebuyer Perks program helps employees navigate the home searching, buying, selling, and refinancing processes and provides valuable financial benefits to encourage, enable, and support home ownership.

Company Overview