Data Scientist, FP&A Solutions
Job Requisition ID #
26WD100824 Position Overview
We are seeking a Data Scientist to join our growing FP&A Solutions team within the Finance Transformation organization. This role sits at the intersection of finance, data science, and analytics engineering. The Data Scientist will partner closely with FP&A, Finance, Data Engineering, and business teams to automate financial analysis, develop forecasting and predictive models, build scalable data solutions, and improve the quality and speed of financial decision-making.
The ideal candidate combines strong technical skills with financial acumen and can translate complex data into clear recommendations for business and finance leaders.
Responsibilities
-
Partner with FP&A and business leaders to identify opportunities where data science and advanced analytics 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 areas such as revenue, expenses, headcount, bookings, customer behavior, cash flow, and business performance
-
Improve financial forecasting through statistical modeling, machine learning, driver-based forecasting, and scenario analysis
-
Automate recurring FP&A processes, including data preparation, variance analysis, forecast updates, management reporting, and financial performance analysis
-
Perform financial and operational variance analysis to identify key drivers, trends, anomalies, and emerging risks
-
Design scenario and sensitivity models that help leadership understand potential financial outcomes and tradeoffs
-
Integrate financial and operational data from multiple systems into trusted analytical datasets within Snowflake
-
Develop reusable Python libraries, notebooks, pipelines, and analytical frameworks that improve productivity across Finance and Analytics teams
-
Partner with Data Engineering teams to improve data quality, architecture, governance, and performance
-
Translate complex analyses and model outputs into concise insights and recommendations for finance and business stakeholders
-
Establish appropriate model validation, monitoring, documentation, and data-quality controls
-
Promote adoption of data science, automation, and AI capabilities within the Finance organization
Minimum Qualifications
-
5+ years of experience in data science, advanced analytics, financial analytics, FP&A analytics, or a related field
-
Advanced proficiency in Python, including experience with libraries such as pandas, NumPy, scikit-learn, statsmodels, or similar analytical frameworks
-
Advanced SQL skills and hands-on experience working with Snowflake
-
Strong understanding of FP&A concepts, including budgeting, forecasting, variance analysis, financial modeling, management reporting, and scenario planning
-
Experience developing statistical, predictive, or machine-learning models against large financial or operational datasets
-
Experience building automated and reproducible analytical workflows
-
Strong understanding of data modeling, data transformation, and analytical data structures
-
Ability to evaluate data quality and identify inconsistencies, anomalies, and underlying business drivers
-
Strong communication skills with the ability to explain technical concepts and analytical findings to non-technical audiences
-
Demonstrated ability to work across Finance, Data, Technology, and business organizations
-
Bachelor's or master's degree in Data Science, Statistics, Computer Science, Economics, Finance, Mathematics, Engineering, or a related quantitative discipline, or equivalent practical experience
Preferred Qualifications
-
Experience working directly within or closely supporting a corporate FP&A organization
-
Experience with financial forecastin