AI Analyst Position Available In Fulton, Georgia

ABM’s AI Implementation team turns cutting-edge data science into real-world impact across our service lines. Reporting to the Director of AI Implementation, the AI Analyst supports every phase of the AI lifecycle—from data exploration and hypothesis design through pilot measurement and long-term performance monitoring. You’ll partner closely with Emerging Tech, the Products, Partnerships & Innovation team, and business-unit stakeholders to ensure each solution delivers measurable value and scales smoothly across ABM’s nationwide footprint.

Pay:

$ 90,000.- $100,00.00 The pay listed is the salary range for this position. Any specific offer will vary based on the successful applicant’s education, experience, skills, abilities, geographic location, and alignment with market data. You may be eligible to participate in a Company incentive or bonus program.

Benefit Information:

ABM offers a comprehensive benefits package. For information about ABM’s benefits, visit ABM Team Member Benefits | Staff & Management Core Responsibilities Responsibility Example Deliverables Data Preparation & Exploration – Collect, clean, and transform data from IoT devices, work-order systems, and operational datasets to make them AI-ready. Curated robotics telemetry dataset; feature-store tables Pilot Experimentation & Analysis – Design tests, define success metrics, and analyze results for AI pilots in partnership with Emerging Tech and PPI. A/B-test report for predictive cleaning model Model Performance Monitoring – Build automated dashboards and alerts for drift, accuracy, latency, and ROI once solutions go live. Real-time dashboard tracking digital-twin anomaly detector Reporting & Visualization – Create concise visual stories and presentations for executive updates, stage-gate reviews, and frontline adoption materials. Monthly KPI deck; Power BI executive scorecard Research & Benchmarking – Evaluate open-source models, SaaS platforms, and academic literature to inform build-vs-buy decisions and roadmap priorities. Competitive scan of small language-model vendors Process Improvement & Governance – Document data lineage, contribute to MLOps best practices, and ensure compliance with security and privacy standards. Model card & data-provenance documentation Preferred Qualifications Experience with facilities management, robotics, IoT, or computer-vision datasets. Familiarity with cloud ML services (AWS SageMaker, Azure ML, or GCP Vertex AI) and DevOps pipelines. Exposure to large language models, prompt engineering, and vector-database retrieval. Knowledge of experiment-tracking tools (MLflow, Weights & Biases) and MLOps frameworks. Required Qualifications Bachelor’s degree in Analytics, Computer Science, Engineering, Mathematics, or a related field. 2-4 years’ experience in data analytics, business intelligence, or applied AI projects. Proficiency with SQL and Python (Pandas, NumPy, scikit-learn); familiarity with Jupyter, Git, and cloud data warehouses. Working knowledge of machine-learning workflows (feature engineering, model training, validation, and monitoring). Experience building dashboards in Power BI or Tableau and communicating technical insights to non-technical audiences. Strong quantitative reasoning, experimental-design, and storytelling skills. Why

ABM & AI

Implementation? You’ll join a fast-moving team that blends startup agility with the resources of a Fortune 500 leader. From optimizing autonomous floor-scrubbing robots to generating real-time energy-savings recommendations, you’ll see your analyses turn into tangible outcomes across airports, hospitals, stadiums, and more. If you thrive on translating data into action and want to shape the future of smart facilities, we’d love to meet you.