This position is not elegible for employment visa sponsorship or transfer sponsorship now or in the future.
- Direct Company Sponsorship: Such as H-1B, J-1, or TN visas.
- Employer of Record: Listing Fusemachines as the immigration employer on any government documentation.
- Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT).
About the RoleWe are seeking a Data Scientist to support Financial Planning & Analysis by developing forecasting models, analytical tools, and data-driven insights that improve financial planning and business decision-making.
This role combines financial analysis, statistical modeling, machine learning, and data engineering. The ideal candidate understands how financial statements and business drivers interact and can translate complex data into practical recommendations for finance and executive stakeholders.
Key Responsibilities- Develop predictive models for revenue, expenses, cash flow, profitability, and other key financial metrics.
- Build driver-based forecasting and scenario-planning models to support annual budgets, rolling forecasts, and long-range planning.
- Analyze historical performance, operational drivers, and external factors to identify trends, risks, and opportunities.
- Improve forecast accuracy by applying statistical methods, machine learning, and time-series modeling.
- Perform variance analysis to explain differences between actuals, budgets, forecasts, and prior periods.
- Develop sensitivity analyses and simulations to evaluate alternative business scenarios.
- Partner with finance, accounting, operations, sales, and other business teams to define analytical requirements and success measures.
- Create dashboards and automated reporting tools that provide visibility into financial and operational performance.
- Integrate and analyze data from ERP, CRM, financial planning, and operational systems.
- Identify data quality issues and work with technical and business teams to improve financial data reliability.
- Present analytical findings and recommendations to finance leaders and senior executives.
- Document models, assumptions, data sources, methodologies, and validation results.
- Support the responsible use of machine learning and generative AI within finance workflows.
Required Qualifications- Bachelor's degree in Data Science, Statistics, Economics, Finance, Mathematics, Computer Science, or a related field.
- 7+ years of experience in data science, financial analytics, business analytics, or a related role.
- Proficiency in Python and SQL.
- Experience with statistical analysis, predictive modeling, and time-series forecasting.
- Understanding of budgeting, forecasting, variance analysis, and financial performance management.
- Ability to work with large, complex datasets from multiple systems.
- Experience developing dashboards with tools such as Power BI, Tableau, or Looker.
- Strong analytical, problem-solving, and quantitative reasoning skills.
- Ability to translate technical findings into clear business and financial recommendations.
- Strong written and verbal communication skills.
Preferred Qualifications- Experience working directly within an FP&A, corporate finance, or strategic finance team.
- Understanding of income statements, balance sheets, cash flow statements, and management reporting.
- Experience with forecasting techniques such as regression, ARIMA, exponential smoothing, gradient boosting, or probabilistic forecasting.
- Experience with financial planning platforms such as Anaplan, Adaptive Planning, Oracle EPM, SAP Analytics Cloud, or similar tools.
- Familiarity with ERP and financial systems such as SAP, Oracle, NetSuite, or Microsoft Dynamics.
- Experience with cloud data platforms such as Snowflake, Databricks, AWS, Azure, or Google Cloud.
- Familiarity with scenario simulation, optimization, causal inference, or sensitivity analysis.
- Experience deploying analytical models into production environments.
- Knowledge of data governance, model monitoring, and financial control requirements.
