The Experience

We are seeking a Manager/Sr. Analyst, Finance Data Science & Predictive Analytics to help build and scale advanced analytics, machine learning, and AI-driven forecasting capabilities within Financial Planning & Analysis (FP&A). This role will partner closely with finance and data teams to develop predictive models, automate insights, and enhance the accuracy of financial planning and decision-making. The ideal candidate combines strong technical expertise with business acumen and thrives in a fast-paced, highly collaborative environment.

What You'll Actually Be Doing

• Develop and deploy predictive models that improve financial forecasting, planning, and business performance visibility.

• Partner with FP&A teams to identify high-impact use cases and translate business challenges into scalable analytics solutions.

• Establish foundational data pipelines, model governance, and performance monitoring processes to support enterprise-grade forecasting capabilities.

• Generate actionable insights from financial and operational data to support strategic decision-making.

• Drive adoption of AI, machine learning, and automation solutions across Finance in partnership with FP&A, and Data teams.

• Build self-service analytics and reporting capabilities that improve stakeholder access to trusted financial and business performance metrics.

• Ensure data integrity, reconciliation, and consistency across multiple systems and data sources.

• Communicate analytical findings and recommendations to finance leadership and cross-functional stakeholders.

You're Our Person If...

• 4+ years of experience in Finance Analytics, Data Science, FP&A, Business Intelligence, or related fields for Sr. Analyst level; 7+ years of experience in Finance Analytics, Data Science, FP&A, Business Intelligence, or related fields for Manager level.

• Bachelor's degree in Finance, Economics, Statistics, Computer Science, Engineering, or a related discipline or equivalent relevant experience required. Experience will be evaluated based on the Core Competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.)

• Strong hands-on experience with SQL and Python, including building and deploying analytical models.

• Experience working with cloud data platforms and modern analytics environments (e.g., GCP, Snowflake, BigQuery).

• Familiarity with machine learning techniques, predictive modeling, and AI/LLM-based applications.

• Experience with BI and observability tools such as Tableau, Looker, Amplitude, Datadog, or similar platforms.

• Strong data validation and reconciliation skills across large, complex datasets

• Ability to translate technical concepts into business insights for non-technical audiences.

• Self-starter who is comfortable operating in ambiguity, building new capabilities from the ground up, and influencing without direct authority.

Even Better If...

• Experience within SaaS or technology organizations

This role is hybrid and goes into the office 3 days per week.