Data Scientist (AI/ML)

BillGO, Inc.-posted 1 day ago

$102,000 - $146,900/Yr

Full-time • Mid Level

Fort Collins, CO

101-250 employees

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We’re looking for a Data Scientist with deep AI and machine learning expertise to help shape the future of data-driven innovation in fintech. You’ll work on developing intelligent systems that power risk modeling, fraud prevention, customer insights and targeting, and payment optimization. Your models will have a direct impact on financial decisions, operational efficiency, and customer trust across our products.

AI-Driven Insights: Develop and deploy advanced machine learning models to optimize customer targeting, payment monitoring and growth and operational efficiency opportunities.
Predictive Modeling: Build forecasting models to improve transaction accuracy, detect anomalies, and assess financial risk.
Data Engineering & Feature Design: Clean, transform, and model large, high-velocity financial datasets with attention to data integrity and compliance.
AI Product Integration: Collaborate with Product to integrate AI solutions into production systems for real-time financial decisioning.
Experimentation: Lead A/B tests and model performance evaluations to validate model effectiveness and regulatory compliance.
Communication: Translate technical findings into actionable insights for business leaders and compliance teams.
Research & Innovation: Stay on top of advancements in generative AI, LLMs, and financial AI applications to guide innovation strategy.

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field.
3+ years of experience in a data science or AI-focused role within fintech, banking, or payments.
Expertise in Python, machine learning frameworks (scikit-learn, TensorFlow, PyTorch), and data pipelines.
Strong background in supervised/unsupervised learning, anomaly detection, NLP, and generative AI.
Familiarity with financial data structures, regulatory standards (e.g., PCI-DSS, GDPR), and model governance.
Experience with cloud platforms such as Snowflake for ML deployment.

Experience in fraud analytics, risk scoring, or payment decision models.
Understanding of MLOps and continuous model monitoring in regulated environments.
Familiarity with financial transaction data, open banking APIs, or real-time payments systems.
Experience developing LLM-powered assistants or AI copilots for financial operations or support.
Strong data storytelling and visualization skills (Tableau preferred).

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