1 day ago
Remote, United StatesStaff+
Responsibilities
- Build and maintain Python data pipelines that ingest, clean, transform, and validate large datasets into analysis-ready data and ML features.
- Develop, evaluate, deploy, monitor, and retrain machine learning models for propensity, churn, segmentation, forecasting, and related use cases.
- Deploy models in AWS for batch and real-time scoring and monitor model performance and drift.
- Design and evaluate LLM prompts and integrate Generative AI capabilities into existing applications.
- Design and analyze A/B tests, measure business impact, and communicate results to product and marketing partners.
- Lead technical design discussions and code reviews, mentor engineers and analysts, and establish ML engineering best practices.
- Partner with database engineering, product management, and InfoSec to build secure, compliant solutions for sensitive consumer data.
- Use AI coding assistants and agentic workflows while reviewing and refining generated output.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field, with demonstrated experience in data science, machine learning engineering, or applied AI and production models.
- Strong Python skills for data engineering and machine learning, including pandas, NumPy, scikit-learn, PySpark, and Jupyter notebooks.
- Experience building data pipelines and processing large datasets with Spark, Redshift, or similar technologies, plus expert SQL skills.
- Hands-on experience with XGBoost, TensorFlow, PyTorch, or similar ML frameworks.
- Experience operationalizing ML models through deployment, monitoring, retraining, and release practices using tools such as SageMaker, MLflow, Docker, or similar technologies.
- Experience running data and ML workloads in AWS, including services such as S3, Glue, Lambda, and Bedrock.
- Experience with LLMs such as Claude or OpenAI GPT, including prompt design, evaluation, and production deployment of Generative AI solutions.
- Strong grounding in statistics, experimental design, and hypothesis testing.
- Production ownership experience including code review, release management, mentoring, and explaining technical results to non-technical partners.
- Experience with RAG workflows, vector stores, MCP server integrations, LLM fine-tuning, Airflow, Step Functions, or regulated consumer data such as credit and financial services is preferred.
Benefits
- Inclusive culture grounded in ownership, customer focus, and respect.
- Professional development through learning experiences and opportunities to leverage individual strengths.
- Competitive compensation, benefits, and rewards programs.
- People-first work environment with work/life balance, employee resource groups, and social events.
Tech Stack
Categories
About FICO
FICO (Fair Isaac Corporation) builds enterprise decision-management software, analytics, and the FICO Score used by lenders to assess consumer credit risk. It sells B2B software, cloud services, and scoring products to banks, insurers, telecoms, and other regulated industries, plus consulting. Founded in 1956 and headquartered in Bozeman, Montana, FICO is a public company on the NYSE; the FICO Score is used by most top U.S. lenders and available in 40+ countries.