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.

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 forecasting, time-series analysis, driver-based planning, Monte Carlo simulation, or scenario modeling Experience