Strategic Analytics Principal

Datasite•New York, NY

1d•$118,800 - $207,200•Hybrid

About The Position

As the Strategic Analytics Principal, you will be a hands-on member of the Data & Analytics team within the CFO organization. This is a role for an expert generalist, someone with the analytical depth to master any problem and the range to own the outputs, actions, and tools that come out of the work. Your primary mission is to deliver strategic insights and drive data analytics solutions, turning business questions and opportunities into data-driven recommendations and tools that leadership can trust and act on. You will spend most of your time in the data — querying, modeling, analyzing, and building — and you will actively leverage AI tools to drive greater business value and unlock innovation.

Requirements

Advanced Excel and SQL: spreadsheet mastery and expert at data querying and modeling data based on problem/project requirements.
Extensive expertise in developing and applying advanced analytics to interpret complex data, uncover trends, and generate actionable insights that inform strategic decision-making.
Proficient in creating impactful presentations, including advanced PowerPoint features and storytelling techniques.
Advanced, hands-on experience using AI tools (e.g., Claude, Codex, Cortex, Copilot, etc.) to improve speed, quality, automation, and innovation.
Natural ability to take a complex problem or high-density technical architecture and simplify it for executive use.
Confident presenting to senior leaders — ability to use data and narrative to make a clear recommendation and field pushback.
Understanding of the levers of a technology business – SaaS economics, product performance, revenue forecasting, financial analysis, etc.
Demonstrated ownership and entrepreneurial mindset by proactively identifying opportunities, driving initiatives end-to-end, and delivering impactful results in dynamic environments.
Think like a product owner — balancing user needs, technical trade-offs, and business value.
Bachelor’s degree or equivalent in a quantitative discipline such as engineering, mathematics, statistics, business, economics, etc.
5+ years of experience in data, analytics, financial planning and analysis, data products, or management consulting.
Superior presentation and communication skills with a proven track record of delivering data stories and strategic recommendations to a leadership audience.
Experience building and managing complex spreadsheet-based quantitative models.
Experience building or owning data/BI/AI products and solutions.
Advanced Excel, data modeling, and statistical analysis.
SQL.
At least one BI/visualization tool (e.g., Power BI).
Hands-on use of AI/GenAI tools (e.g., Claude, Codex) in daily work.

Nice To Haves

MBA or Master’s in a quantitative discipline such as Finance, Economics, Analytics, etc. preferred.
Python.
Snowflake.
dbt or semantic-layer modeling.
Streamlit.
Salesforce/ERP data.
Experience building LLM- or agent-based tools.

Responsibilities

Serve as a go-to analyst for stakeholders across Finance on analytics projects.
Lead and execute high-impact deep dives into complex topics like revenue leakage, product profitability, and margin optimization.
Structure the problem, identify the levers, and define the success criteria when business stakeholders don't know where to start.
Run deep-dive discovery when a KPI fluctuates, identifying root causes across sales, product, usage, and financial data.
Build and present a clear data story and strategic narrative, synthesizing complex analytical findings into crisp, high-impact decks that lead with the "So What" and end with a clear call to action.
Leverage AI tools — copilots, skills and plugins, LLM-assisted SQL and analysis, and workflow automation — to accelerate delivery, cut manual effort, and prototype new analytical approaches.
Define, standardize, and govern the core metrics for the Finance organization, ensuring "metric consistency" across the company.
Ensure the calculations and definitions connecting raw data to models, reports and solutions are sound and consistent.
Own data products and solutions — data & BI tools, analytics agents, decision engines — across their lifecycle in close partnership with data and analytics engineers, platform architects, and technology teams.