Data Analyst

Requirements 3–7 years of experience in a data, analytics, financial modeling, or systems-focused role (Total Rewards experience a plus, not a requirement) Advanced proficiency in Excel/Google Sheets — you can build complex models from scratch without hand-holding Experience building dashboards and visualizations in tools like Tableau, Power BI, Looker, or similar Demonstrated ability to work with large, sensitive datasets with accuracy and discretion Strong analytical instincts — you can spot what the data is really saying, not just what was asked You’ll be working with some of the most sensitive and strategically important data in the company You’ll have real creative latitude to build new tools and processes — not just maintain existing ones You’ll partner closely with senior Total Rewards leaders and have visibility into compensation and benefits strategy This is a role where strong technical work directly translates to business impact We’re looking for problem‑solving, opportunity‑finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high‑performing team that believes in each other, come build with us at Crusoe You don’t need to come from a Compensation or Benefits background. What matters most is that you’re a strong modeler, a natural systems thinker, and someone who gets excited about building smarter, more automated ways to work with data (Desirable) Experience with HCM platforms (Workday strongly preferred) and their reporting/analytics layers (Desirable) Hands‑on experience building AI‑enabled tools or workflows — whether using APIs, LLMs, low‑code platforms, or custom scripts (Desirable) Proficiency in Python, SQL, or R for data manipulation and automation (Desirable) Familiarity with compensation or benefits data structures, even if not in a dedicated Comp/Benefits role (Desirable) Experience with compensation survey tools (Radford, WTW, Mercer, etc.) a plus What the job involves We’re looking for an analytically sharp, technically creative Senior Data & Reporting Systems Analyst to join our Total Rewards team This role sits at the intersection of people data, financial modeling, and systems intelligence — and is a great fit for someone who loves turning complex, sensitive datasets into clear insights and scalable tools Reporting & Systems Expertise: Become a deep subject matter expert in reporting across our HCM, compensation, and benefits platforms (e.g., Workday, Radford/WTW, market pricing tools, benefits administration systems) Own the design, development, and maintenance of dashboards and recurring reports that surface Total Rewards data for HR, Finance, and business partners Partner with HR Systems and IT to improve data quality, integrations, and reporting infrastructure Financial & Compensation Modeling: Build and maintain financial models to support compensation planning cycles, benefits cost analysis, merit and equity budgeting, and headcount forecasting Conduct benchmarking analyses using survey data and internal pay data to support compensation reviews and program design decisions Handle and safeguard sensitive employee data with the highest degree of discretion and compliance Automation & AI‑Enabled Tooling: Proactively identify manual, repetitive workflows and build automated solutions to replace them Develop or contribute to AI‑enabled tools that improve team efficiency — whether that’s prompt‑based workflows, LLM‑assisted data parsing, or intelligent reporting triggers Bring a creative, builder mindset to tooling: if a better process doesn’t exist, you design it Collaboration & Insight: Translate complex data into clear narratives and recommendations for non‑technical stakeholders Support ad hoc analytical requests from Total Rewards, HR leadership, and Finance Document methodologies, data dictionaries, and model logic to ensure reproducibility and knowledge sharing #J-18808-Ljbffr