Job Requisition ID #26WD100824
Position OverviewWe 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 forecasting, time-series analysis, driver-based planning, Monte Carlo simulation, or scenario modeling
- Experience developing production-quality analytical solutions using Snowflake and Python
- Familiarity with Snowpark for Python, dbt, orchestration tools, or modern data-engineering practices
- Experience with financial planning platforms such as Adaptive Planning, Anaplan, Oracle EPM, or similar systems
- Experience with visualization and BI platforms such as Power BI, Tableau, or Looker
- Experience applying machine learning, generative AI, or intelligent automation to Finance use cases
- Familiarity with software development practices including Git, testing, CI/CD, code review, and version control
- Experience working in a large, global, or matrixed organization
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