Finance Project Manager

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.

Analytics Data Product Manager – Finance Transformation

Level: Mid to Senior Level (8–10+ years experience)

Job Summary

This is for a Analytics product manager role who will be working with client's finance tech/business stakeholders. Candidates will only be confirmed after client interviews

Position Overview:

Latentview Analytics is seeking a strategic and technical Analytics Data Product Manager to bridge the gap between our Finance Business Sub-teams, Technology, and Central IT. You will lead the "Decision Support COE" vision, specifically driving the implementation of a governed Microsoft Fabric semantic layer between our Snowflake data warehouse and Power BI reporting suite. Your primary mission is to transform EA Finance from reactive manual reporting to proactive decision support by building an "AI-Ready" data ecosystem.

Key Responsibilities:

• Strategy & Liaison: Act as the primary liaison between Controllership, FP&A sub-teams, and Enterprise IT to define and prioritize the finance data product roadmap.
• Fabric Semantic Layer Implementation: Oversee the transition of the "Silver" and "Gold" data layers from IT to the Finance team, implementing Microsoft Fabric to eliminate data replication and address current Power BI capacity blowups.
• Metric Governance: Define and lock a "Certified Semantic Layer" (math and business logic) within the Governance Mesh process, ensuring zero discrepancies for KPIs like Net Revenue and EBITDA across all reports.
• AI Agentic Roadmap: Lead the movement toward a "Governed AI Mesh" architecture, deploying 1–3 AI agents per user to automate workflows like variance commentary, invoice reconciliation, and what-if scenarios.
• User Enablement: Conduct "Decision Support Bootcamps" to upskill GFC analysts, moving them from "shadow IT" spreadsheet work to using pre-certified low-code Fabric metrics.
• Performance Optimization: Address current performance bottlenecks in DirectQuery execution to ensure real-time, drill-down visibility from board-level figures to source transactions.

Required Qualifications:

• Domain background in Corporate Finance, specifically in Controllership or FP&A functions. Either prior experience in working with Finance org or have Finance background via academics.
• Data Experience: Technical proficiency in the Snowflake + Power BI stack; experience with Microsoft Fabric (OneLake, Direct Lake) is highly preferred.
• Data Governance: Experience implementing data catalogs (Purview and others) and data lineage tracking to build trust in large-scale data environments.

Preferred Qualifications:

• Masters in Finance or CFA (Chartered Financial Analyst) background or equivalent senior-level finance certification.
• AI/ML Integration: Preferred proven experience (or strong theoretical knowledge) in implementing AI agents, LLMs, or agentic frameworks (e.g., Google Gemini, Azure OpenAI) for workflow automation.
• Experience with Google Cloud Platform (GCP), specifically leveraging BigQuery Omni or Gemini in a multicloud architecture to avoid vendor lock-in.
• Experience in the gaming or high-tech sectors, managing complex high-volume transactional data (e.g., Oracle R12, RevPro, Workday).
• What Success Looks Like in 12 Months
• Reduction of reporting lead times from months/weeks to days/hours.
• A unified, certified data model for game-level P&L that serves as the single version of financial truth for the CFO office.
• Successful pilot of the first set of autonomous AI agents for automated financial summaries.

At LatentView Analytics, we value a diverse, inclusive workforce and provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual's race, colour, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.