Senior AI Product Manager - Enterprise Apps - Zoominfo

About The Role:

• The Enterprise Apps AI Center of Excellence (CoE) is a recently established team operating with startup-like agility to generate substantial value through Artificial Intelligence.
• Beyond merely enhancing efficiency, our focus is on developing innovative AI solutions that unlock novel capabilities and insights for the CFO and CRO organizations. Our mission is to transform processes, optimize strategic decision-making, and deliver significant value through advanced AI applications. This team will be responsible for identifying, analyzing, developing, and deploying high-impact use cases. The ultimate objective is to empower the Office of the CFO with state-of-the-art AI, facilitating more strategic and effective operations.
• As the Product Manager, you will spearhead our team in the conceptualization, development, and deployment of impactful AI solutions that revolutionize financial processes. You will be accountable for the entire AI solution lifecycle, encompassing ideation, requirements gathering, development, implementation, and ongoing support. This role necessitates leadership of a geographically diverse team situated in the US and India.
• Identify and conduct Proof of Concept (POC) for efficiency opportunities in software development, software optimization/tech debt reduction, QA, UAT, Unit Testing, and Regression Testing.
• A critical aspect of this position involves influencing business units regarding potential AI features across marketing, sales, contracts, order management, and finance functions, leveraging our internal innovations to shape future solution offerings.

What you’ll do:

• Design and implement scalable full-stack solutions that integrate with finance business applications.
• Proactively research industry trends to identify and evaluate potential AI applications within finance operations.
• Analyze Marketing, Sales, and Finance processes specific to a SaaS company to identify areas amenable to AI enablement.
• Determine the most critical and feasible AI use cases, considering technical requirements and data availability. 
• Clearly articulate the potential Return on Investment (ROI) and benefits of proposed AI solutions.
• Develop compelling proposals that detail AI concepts, data-supported benefits, required resources, and the technical rationale.
• Lead the development and testing of AI initiatives, providing expertise in data analysis, machine learning methodologies, experimental design, solution architecture, and success measurement.
• Collaborate with technology, product, and data teams to seamlessly integrate validated AI solutions into existing finance workflows, clearly communicating technical details.
• Provide technical leadership and mentorship to the engineering team, fostering a culture of innovation and continuous learning.

Other Qualifications:

• Solid understanding of statistical principles, including hypothesis testing, regression analysis, time series forecasting, and other relevant techniques.
• Comprehensive knowledge of machine learning algorithms (supervised, unsupervised, reinforcement learning) and their model selection, training, evaluation, and deployment.
• Understands data pipelines, data warehousing, and data governance pertinent to building and deploying ML models.
• Stays abreast of the latest AI research and its potential applications in finance.
• Identifies strategic AI opportunities to enhance finance functions.
• Develops clear implementation plans for AI initiatives.
• Quantifies potential financial benefits (ROI, cost reduction, efficiency gains) using data-driven forecasting.
• Clearly and effectively communicates complex AI/ML concepts to both technical and non-technical stakeholders, including model logic and performance metrics.
• Possesses a deep appreciation for data modeling, data correctness, integrity, and traceability, particularly in regulated environments.
• Understands common patterns in financial reconciliation, anomaly detection, and structured data modeling.
• Enjoys partnering with Finance and Engineering stakeholders to translate operational requirements into clean, auditable datasets.

What you bring:

• Minimum of 8 years of hands-on experience in efficiently driving data science or machine learning use cases, with a primary focus on finance and accounting domains.
• Strong understanding of the Software Development Life Cycle (SDLC) and standard methodologies for coding, design, testing, and deployment.
• Bachelor's or Master’s degree in Computer Science, Software Engineering, Statistics, Applied Mathematics, or an equivalent quantitative field.
• Excellent technical, problem-solving, and communication skills.
• Ability to analyze and resolve complex technical issues expeditiously in a high-pressure environment.
• Experience in working with and presenting compelling proposals to executives.
• Experience working with ERP applications such as SAP, Workday, or NetSuite is advantageous.

Technical Skills

• Strong proficiency in modern programming languages (e.g., Java, Python) and frameworks (e.g., React, Node.js). Exposure to integration platforms such as Boomi.
• Strong Excel skills are required. Experience with SQL, Tableau, or other BI tools for extracting and visualizing data is a plus.
• Deep expertise in Neural Networks, Deep Learning, Conversational AI (e.g., ChatBots, IVA, AgentAssist), and NLP (LLMs, Transformers, RNNs, Semantic Search), including Prompt Engineering.
• Hands-on experience with AIOps, MLOps, and DataOps in building production-grade AI/ML pipelines with KubeFlow, MLFlow, and AutoML on cloud platforms (AWS, Azure, GCP).

Hands-on experience with AI-powered search (vector database, semantic search) and Microservices development - Java, Python, Spring Boot, and NoSQL.