Top 9 Ai data scientist Jobs in Greeley, Co

AI Scientist
BillGO, Inc. —Fort Collins, CO
- $132,800 - $196,500 a year
- Full-time
- Computer Science
- 5 years
- Databases
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AI Data Scientist
BillGO, Inc. —Fort Collins, CO
- $102,000 - $146,900 a year
- Full-time
- Computer Science
- Mid-level
- 3 years
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Data Scientist AI/ML
BillGO, Inc. —Fort Collins, CO
- $102,000 - $146,900 a year
- Full-time
- Computer Science
- Mid-level
- 3 years
- Health insurance
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Senior AI Engineer
Hewlett Packard Enterprise —Fort Collins, CO
- $144,000 - $273,000 a year
- Full-time
- Computer Science
- Bachelor of Science
- Mid-level
AI Data Analytics Engineer
BillGO, Inc. —Fort Collins, CO
- $102,000 - $146,900 a year
- Full-time
- Mid-level
- 3 years
- SQL
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AI & ML Software Engineer
Hewlett Packard Enterprise —Fort Collins, CO
- $144,000 - $273,000 a year
- Full-time
- Office
- Continuous improvement
- Fair chance
18h

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AI Scientist

BillGO, Inc. -
Fort Collins, CO

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Job Details

Full-time
$132,800 - $196,500 a year

Qualifications

AI models
Model deployment
Model training
Machine learning libraries
Machine learning frameworks

Full Job Description

AI Scientist: Shape the future of payments powered by AI/ML

BillGO is building future of B2B payments, helping small businesses get paid faster, operate smarter, and stay focused on what matters, while BillGO accelerates their payments and automate the complexity end-to-end.

AI/ML is a core capability at BillGO, not a side project. We use AI to:

Eliminate manual work for customers and internal teams
Automate decisions and workflows inside payment flows
Empower small teams to deliver 10X outcomes at 1X cost

We are hiring an AI Scientist who can turn this belief into shipped, production-grade systems. This is a highly influential, hands-on role. You will work directly with the CTO and senior leaders across product, engineering, business and operations to identify high leverage opportunities and deliver AI/ML solutions that materially improve outcomes for small businesses.

The Role

This is a strategic hands-on AI/ML role for a builder who combines:

A strong research foundation
A track record of shipping ML systems into production
A modern, pragmatic AI mindset focused on outcomes, leverage, and velocity

You will own AI/ML systems end-to-end from problem framing through production operations—across both:

Customer-facing AI products for small businesses
Internal AI systems that radically increase BillGO’s operational leverage

What You’ll Do

Customer-Facing AI (Primary)

Build AI/ML solutions embedded directly in B2B payment flows, such as:
Intelligent payment acceleration and prioritization
Cash-flow forecasting and predictive insights
Automated reconciliation, exception handling, and workflow orchestration
Decisioning systems that remove work rather than add alerts
Design models that balance accuracy, latency, explainability, and reliability for business-critical systems
Own model behavior in real-world conditions, not just offline metrics

Internal AI Leverage (Equally Important)

Partner with Engineering, Product, Ops, and Finance to:
Automate internal workflows using ML and LLMs
Replace manual reviews and heuristics with intelligent systems
Reduce cost-to-serve while increasing throughput and quality
Build AI tools that allow small teams to operate like large ones

Responsibilities

End-to-End Ownership

Own the full ML lifecycle: problem definition, data exploration, feature engineering, modeling, evaluation, deployment, monitoring, and iteration
Translate ambiguous business problems into clear ML objectives and success metrics

Production Systems & Operations

Build and maintain production-grade ML systems, including:
Batch and real-time pipelines
Feature generation and data quality checks
Model monitoring, drift detection, retraining, and reliability SLAs
Operate ML systems in mission-critical environments:
Participate in incident response and rapid mitigations
Design safe rollouts, fallbacks, and guardrails
Own models once deployed, including ongoing performance, reliability, and evolution over time

Experiments & Metrics

Design and run experiments (offline and online / A-B testing where applicable) and clearly communicate results and tradeoffs

Collaboration & Architecture

Collaborate deeply with Product and Engineering to embed AI directly into customer and internal workflows
Favor reusable, extensible architectures over one-off models or demos

Strategic Influence

Help shape BillGO’s AI technical direction and standards as the company scales
Help define not just models, but how AI is used responsibly, reliably, and at scale across the company

What You Bring

5+ years of proven experience building and shipping ML systems into production with measurable business impact
Strong foundation in machine learning (modeling, training, evaluation, deployment), statistics, and experimentation
Fluency in Python and modern ML tooling (e.g., PyTorch, TensorFlow, scikit-learn)
Comfortable owning data pipelines and featurization (not dependent on others to make data “model-ready”)
Experience working with large, messy, real-world datasets
Ability to clearly explain models, tradeoffs, and outcomes to non-ML stakeholders
A mindset focused on leverage, simplicity, and results not process or legacy approaches
Hands-on experience with modern AI stacks (LLMs, vector databases, orchestration frameworks)
Ability to think holistically across data, infrastructure, product, and UX
Relentless curiosity with a strong builder’s mindset
Bias toward action, experimentation, and measurable outcomes
Comfortable making decisions with imperfect information
Deep motivation to deliver 10X impact with 1X cost
MS or PhD in CS, ML, Statistics, Applied Math, or a related field or equivalent industry experience
Research experience that informs better decisions but does not slow shipping

Strongly Preferred

Experience in payments, fintech, B2B platforms, or workflow automation
Experience with real-time decisioning systems (latency, throughput, reliability constraints)
Applied experience with foundation models (evaluation, guardrails, fine-tuning, agentic workflows)
Experience designing decision systems, not just predictive models
A track record of replacing complex manual processes with simple, automated systems
Exposure to fraud, risk, or compliance systems.
AI/ML Certifications, Published papers and contributions to the AI/ML Community.

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ai data scientist jobs in greeley, co

AI Scientist

AI Data Scientist

Data Scientist AI/ML

Senior AI Engineer

AI Data Analytics Engineer

AI & ML Software Engineer

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