Lead Data Scientist (AI)

Location: Work from Home, United States

Company

hirify.global is a global analytics software company providing decisioning, credit scoring, fraud detection, and lending solutions to businesses in more than 100 countries.

What you will do

• Build and maintain Python data pipelines that ingest, clean, and transform large datasets into reliable analysis-ready data and ML features.
• Develop, evaluate, deploy, monitor, and retrain machine learning models for propensity, churn, segmentation, forecasting, and other consumer applications.
• Deploy batch and real-time scoring workloads in AWS and establish data quality, model monitoring, drift detection, and retraining automation.
• Design and evaluate LLM prompts and integrate Generative AI capabilities into production applications.
• Design and analyze A/B tests, measure business impact, and communicate results to product and marketing partners.
• Lead design discussions and code reviews, mentor engineers and analysts, and establish ML engineering best practices while partnering with database engineering, product management, and InfoSec.

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, including models running in production.
• Strong Python skills for data engineering and ML, 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 for complex queries.
• Hands-on experience with XGBoost, TensorFlow, PyTorch, or similar ML frameworks.
• Experience operationalizing ML models through deployment, monitoring, retraining, and CI/CD using SageMaker, MLflow, Docker, or similar tools.
• Experience running data and ML workloads in AWS, including S3, Glue, Lambda, Bedrock, or similar services.
• 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.

Nice to have

• 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.

Culture & Benefits

• Inclusive, people-first culture based on ownership, customer focus, and mutual respect.
• Competitive compensation, benefits, and rewards programs.
• Professional development through learning experiences and opportunities to use individual strengths.
• Work/life balance, employee resource groups, and social events.
• Use of AI coding assistants and agentic workflows such as Claude Code, Cursor, and GitHub Copilot is supported, with review and refinement of their output.