FP&A Data Scientist: Forecasting & Automation

Socket.dev; California (MO); Hybrid; USD 109,000 - 196,000; Full time

Job summary

Autodesk is seeking a Data Scientist to join the FP&A Solutions team within the Finance Transformation organization. You will automate financial analysis, develop forecasting models, and build scalable data solutions to improve decision-making across finance and business units.

The role combines finance, data science, and analytics engineering, requiring strong technical skills and financial acumen to translate complex data into actionable insights for leaders.

Qualifications

• 5+ years of experience in data science, advanced analytics, financial analytics, FP&A analytics, or a related field.
• Advanced proficiency in Python, including libraries such as pandas, NumPy, scikit-learn, statsmodels, or similar analytical frameworks.
• Advanced SQL skills and hands-on experience with Snowflake.
• Strong understanding of FP&A concepts, including budgeting, forecasting, variance analysis, financial modeling, management reporting, and scenario planning.

Responsibilities

• Identify opportunities where data science can improve planning, forecasting, and decision-making.
• Develop Python-based analytical models, forecasting solutions, simulations, and automation for financial and operational use cases.
• Build and maintain scalable datasets and analytical workflows using Snowflake, SQL, and Python.
• Develop predictive models for revenue, expenses, headcount, bookings, customer behavior, cash flow, and business performance.
• Improve financial forecasting through statistical modeling, machine learning, and scenario analysis.

Skills

Python

SQL

Snowflake

FP&A knowledge

Machine learning

Education

Bachelor's or Master's in Data Science / Statistics / CS / Economics / Finance

Tools

Snowpark for Python

dbt

Job description

Autodesk is seeking a Data Scientist to join the FP&A Solutions team within the Finance Transformation organization. You will automate financial analysis, develop forecasting models, and build scalable data solutions to improve decision-making across finance and business units.

The role combines finance, data science, and analytics engineering, requiring strong technical skills and financial acumen to translate complex data into actionable insights for leaders.