Senior Technical Delivery Manager

Role Responsibilities - How You Will Make An Impact:

• Orchestrate: Work with clients, the business, and engineers to set strategy and collect and prioritize requirements. Manage requirements documentation, milestone mapping, prioritization, and communication to facilitate project collaboration.
• Execute: Work with data scientists, machine learning engineers, software engineers, and designers to build products that delight our customers. Proactively identify assumptions, dependencies, issues, risks and drive discussions across the team to develop mitigation plans and implementation paths. Maintain compliance with IT and security policies and procedures.
• Strategize: Think widely about potential applications of machine learning and natural language processing techniques, translating capabilities built for individual clients into new features or customization options for our core products.

Relevant Skills and Experience:

• 5+ years of experience in a professional environment, ideally within a SaaS-based company
• Proven success managing large-scale enterprise data integration projects that are highly technical and cross-functional in nature
• Skilled in gathering and prioritizing requirements, leading scope discussions, and aligning on project priorities
• Comfortable working across internal functions (Engineering, Product, Security, Compliance, Customer Experience, etc.) and with external client stakeholders
• Strong technical understanding with the ability to contribute to system design conversations and drive enterprise data and architecture initiatives
• Experience working with DoD or public sector clients and understanding of relevant processes (e.g., FedStart, ATO)
• Must hold an active Top Secret (TS) security clearance; TS/SCI strongly preferred

Bonus Points:

• Familiarity with machine learning workflows and core data science concepts (e.g., classification vs. regression, feature engineering, model selection and tuning, deployment considerations)
• Understanding of ML algorithms, database structures, or data pipeline development
• Background in coding or working closely with engineering teams