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

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Partner with FP&A and business leaders to identify opportunities where data science and advanced analytics can improve planning, forecasting, and decision-making

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Develop Python-based analytical models, forecasting solutions, simulations, and automation for financial and operational use cases

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Build and maintain scalable datasets and analytical workflows using Snowflake, SQL, and Python

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Develop predictive models for areas such as revenue, expenses, headcount, bookings, customer behavior, cash flow, and business performance

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Improve financial forecasting through statistical modeling, machine learning, driver-based forecasting, and scenario analysis

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Automate recurring FP&A processes, including data preparation, variance analysis, forecast updates, management reporting, and financial performance analysis

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Perform financial and operational variance analysis to identify key drivers, trends, anomalies, and emerging risks

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Design scenario and sensitivity models that help leadership understand potential financial outcomes and tradeoffs

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Integrate financial and operational data from multiple systems into trusted analytical datasets within Snowflake

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Develop reusable Python libraries, notebooks, pipelines, and analytical frameworks that improve productivity across Finance and Analytics teams

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Partner with Data Engineering teams to improve data quality, architecture, governance, and performance

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Translate complex analyses and model outputs into concise insights and recommendations for finance and business stakeholders

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Establish appropriate model validation, monitoring, documentation, and data-quality controls

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Promote adoption of data science, automation, and AI capabilities within the Finance organization

Minimum Qualifications

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5+ years of experience in data science, advanced analytics, financial analytics, FP&A analytics, or a related field

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Advanced proficiency in Python, including experience with libraries such as pandas, NumPy, scikit-learn, statsmodels, or similar analytical frameworks

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Advanced SQL skills and hands-on experience working with Snowflake

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Strong understanding of FP&A concepts, including budgeting, forecasting, variance analysis, financial modeling, management reporting, and scenario planning

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Experience developing statistical, predictive, or machine-learning models against large financial or operational datasets

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Experience building automated and reproducible analytical workflows

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Strong understanding of data modeling, data transformation, and analytical data structures

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Ability to evaluate data quality and identify inconsistencies, anomalies, and underlying business drivers

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Strong communication skills with the ability to explain technical concepts and analytical findings to non-technical audiences

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Demonstrated ability to work across Finance, Data, Technology, and business organizations

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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

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Experience working directly within or closely supporting a corporate FP&A organization

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Experience with financial forecastin