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Join Arkham as a Forward Deployed Engineer to drive AI transformation for clients through hands-on data science and AI architecture, delivering impactful solutions.
About Arkham
Arkham is a Data & AI platform that helps large enterprises:- Unify fragmented systems and data
- Build a single source of trusted operational metrics
- Solve complex challenges with AI tailored to their operations
Teams at Circle K and Kimberly-Clark partner with us to deploy AI-powered solutions for sell-out forecasting, pricing and promo analysis, and automated order assignment. With Arkham, they achieve high-impact results fast, creating a strong foundation for long-term AI transformation.
About the Role
As a Forward Deployed Engineer, you help drive the AI transformation journey for our customers. You work hands-on across data science, AI architecture, and implementation, partnering closely with client stakeholders to deliver high-impact solutions. Once a customer's Data Platform is live in Arkham, you help deliver and expand AI use cases. You partner with BI, Finance, Operations, and business stakeholders to:- Identify high-leverage AI opportunities
- Build robust ML and GenAI solutions
- Deploy production-ready systems
- Support adoption across the client organization
You will typically contribute to 1-4 implementations simultaneously, working alongside senior team members.
What You'll Work On
- Build and deploy ML models (like forecasting, optimization, clustering, and anomaly detection models)
- Develop Generative AI workflows
- Implement AI Agents that automate analysis and operational decisions
- Follow best practices for model monitoring, retraining, and governance
- Contribute to the first "Aha" moment: within 2-4 weeks, help deliver an operational AI solution that solves a core business pain point
- Define data requirements and modeling strategies in collaboration with the team
What We Require
- 2-3 years of hands-on Data Science experience
- Experience delivering ML systems into production
- Some exposure to client-facing or stakeholder-intensive environments
- Solid proficiency in Python and SQL
- Experience with forecasting and time-series models
- Experience with supervised and unsupervised ML
- Familiarity with Generative AI and prompt engineering
- Familiarity with AI agents and LLM-based workflows
- Proficiency with Git and collaborative development workflows
- Good understanding of statistical modeling and model evaluation
- Strong communication and collaboration skills