Senior Data Scientist – Platform Optimization (Snowflake / Databricks)

About the Job

FinOpsly is seeking a skilled Data Scientist to join our team. We are developing an AI-native Value-Control™ platform for cloud (AWS, Azure, GCP), data (Snowflake, Databricks), and AI economics. This role focuses on applied optimization science for modern data platforms, working to move enterprises beyond passive cost visibility to outcome-driven control.

Responsibilities:

• Analyze query history, warehouse/cluster utilization, and workload telemetry.
• Build anomaly detection models for cost spikes and performance degradation.
• Develop right-sizing and optimization recommendation engines.
• Translate platform signals into prescriptive, explainable insights.
• Partner with engineering to embed intelligence into customer-facing modules.
• Quantify measurable savings and performance gains.
• Build an advanced optimization and intelligence engine to reduce data platform costs, improve performance, and detect anomalies in real time.

Qualifications:

• 5+ years in Data Science, Applied ML, or Performance Engineering
• Deep expertise in Snowflake (warehouses, clustering, query plans, credit usage) or Databricks (Spark optimization, cluster sizing, Delta Lake, DBU usage)
• Strong SQL + Python (pandas / PySpark / ML libraries)
• Experience with time-series modeling and anomaly detection
• Passion for optimization, automation, and measurable impact

Why This Role Matters:

You will play a key role in helping enterprises achieve intelligent, automated value control, optimizing platform usage, and aligning data spend with performance and business outcomes. If you have a passion for data science, distributed systems, and cloud economics, this is the role for you.