Job Description & How to Apply Below
Company Description
Fin Opsly is an AI-native Value-Control™ platform for cloud (AWS, AZ, GCP), data (Snowflake, Databricks), and AI economics, built to help enterprises move beyond passive cost visibility to active, outcome-driven control. The platform unifies technology spend across cloud infrastructure (AWS, Azure, GCP), data platforms (Snowflake, Databricks), and AI workloads into a single system of action—combining planning, optimization, automation, and financial operations.
Role Description
We are seeking a highly motivated Fin Ops Data Analyst / Data Scientist to join our growing data organization. This role is ideal for early-career professionals who are passionate about data, analytics, and building scalable solutions that drive business impact.
You will work closely with engineering, Fin Ops SMEs, product managers, and business stakeholders to analyze cloud, financial, and operational data. The role combines analytical rigor, technical capability, and curiosity to translate complex datasets into actionable insights.
If you are analytically strong and want hands-on exposure to real-world AWS, Azure, GCP and Snowflake datasets, this role offers accelerated growth in cloud economics and cost optimization.
What you will do:
Analyze AWS, Azure and GCP billing and Snowflake usage data
Identify cost drivers, inefficiencies, and optimization opportunities
Build SQL-based financial models and KPIs
Support anomaly detection and forecasting for cloud spend
Contribute to automation of cost optimization insights
What you bring:
3+ years of experience in financial data analysis, or data analytics in a cloud-native environment.
Hands-on experience analyzing AWS CUR, Azure Billing Exports, or similar cloud consumption datasets preferred
Strong proficiency in SQL, including complex joins, window functions, performance optimization, and building reusable analytical views.
Experience working in Snowflake or comparable cloud data warehouse environments.
Practical understanding of Fin Ops concepts:
Preferred
Ability to build and interpret financial KPIs and cost efficiency metrics.
Proficiency in Python (Pandas, Num Py) for large dataset analysis and automation.
Experience performing cost anomaly detection, trend analysis, and spend forecasting.
Ability to translate technical cloud usage data into clear financial narratives for stakeholders (engineering, finance, leadership).
Strong attention to detail, especially when working with reconciliation, billing validation, and financial accuracy.
Solid foundation in statistics and data analysis
Curiosity about cloud platforms and financial analytics
Ability to work independently in a fast-paced startup
What You'll Gain:
Exposure to enterprise-scale cloud billing datasets
Hands-on experience with Snowflake and cloud cost engineering
Real impact on financial decision-making for customers
Accelerated path into Fin Ops Data Science or Cloud Optimization Engineering
If you are excited about applying data science to real financial outcomes in cloud and AI environments, we would like to connect.
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