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Manager Data Scientist Finance Jobs (NOW HIRING)

Figma is a company dedicated to making design accessible to all, and they are seeking a Finance Data Scientist to enhance their financial data systems. This role involves building data foundations ...

Figma is growing our Finance Data Science team at a pivotal moment in the company's evolution. As a ... PTO is subject to manager approval. Additional benefits may include company recharge days, cell ...

Figma is a company focused on making design accessible to all, and they are seeking a Finance Data Scientist to enhance their financial data systems. This role involves building data foundations for ...

Figma is growing our Finance Data Science team at a pivotal moment in the company\'s evolution. As ... PTO is subject to manager approval. Additional benefits may include company recharge days, cell ...

Manager, Data Scientist Data is at the center of everything we do. As a startup, we disrupted the ... in their financial lives. Team Description In Capital One's Model Risk Office, we defend the ...

Manager, Data Scientist Data is at the center of everything we do. As a startup, we disrupted the ... in their financial lives. Team Description In Capital One's Model Risk Office, we defend the ...

Manager, Data Scientist Data is at the center of everything we do. As a startup, we disrupted the ... in their financial lives. Team Description In Capital One's Model Risk Office, we defend the ...

This function manages analytic data platforms, the access, design and implementation of reporting ... Data Science applies base, scientific methodologies from various disciplines, techniques and tools ...

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Manager Data Scientist Finance information

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$46K

$165K

$243.5K

How much do manager data scientist finance jobs pay per year?

As of Aug 5, 2026, the average yearly pay for manager data scientist finance in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is the difference between Manager Data Scientist Finance vs Data Scientist Finance?

AspectManager Data Scientist FinanceData Scientist Finance
Required CredentialsBachelor's or Master's in Finance, Data Science, or related field; often leadership experienceBachelor's or Master's in Data Science, Statistics, or related field; technical skills emphasized
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersFocuses on data analysis, model development, and technical problem-solving
Employer & Industry UsageFinancial institutions, banks, investment firmsFinancial firms, fintech companies, banks

The main difference is that a Manager Data Scientist Finance oversees teams and projects, requiring leadership skills, while a Data Scientist Finance primarily focuses on technical data analysis and modeling. Both roles are common in financial services, but the manager role involves more strategic and managerial responsibilities.

How does a manager data scientist in finance typically collaborate with cross-functional teams to drive data-driven decision making?

As a Manager Data Scientist in Finance, you will frequently collaborate with professionals from risk, compliance, IT, and business strategy departments. Your role involves translating complex data analyses into actionable insights for stakeholders who may not have a technical background. Regular meetings, workshops, and presentations are common, as you guide teams on leveraging predictive models and analytics for financial forecasting, fraud detection, and process optimization. Effective communication and the ability to bridge the gap between data science and business strategy are essential for success in this collaborative environment.

What does a manager data scientist in finance do?

A Manager Data Scientist in Finance leads a team of data scientists to analyze financial data, build predictive models, and provide insights that support business decisions. They oversee data-driven projects related to risk analysis, fraud detection, investment strategies, and process optimization. This role often involves collaborating with stakeholders across the organization to identify opportunities for leveraging data and ensuring that analytical solutions align with business goals. Additionally, they are responsible for mentoring team members and ensuring data quality and compliance with regulations.

What are the key skills and qualifications needed to thrive as a manager data scientist in finance?

To thrive as a Manager Data Scientist in Finance, you need advanced expertise in statistics, financial modeling, and machine learning, typically supported by a degree in a quantitative field and relevant industry experience. Familiarity with programming languages like Python or R, data visualization tools, and financial analytics platforms such as Bloomberg or SAS is crucial. Exceptional leadership, communication, and problem-solving skills distinguish top performers in this role. These skills and qualities are vital for extracting actionable insights from complex data, guiding teams, and driving strategic decision-making in the financial sector.
What cities are hiring for Manager Data Scientist Finance jobs? Cities with the most Manager Data Scientist Finance job openings:
What are the most commonly searched types of Data Scientist Finance jobs? The most popular types of Data Scientist Finance jobs are:
What states have the most Manager Data Scientist Finance jobs? States with the most job openings for Manager Data Scientist Finance jobs include:

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Job description

Job Summary:
Figma is a company dedicated to making design accessible to all, and they are seeking a Finance Data Scientist to enhance their financial data systems. This role involves building data foundations for financial reporting and collaborating closely with various teams to ensure the accuracy and effectiveness of financial metrics.
Responsibilities:
• Own and improve the data models that power Figma's financial reporting, including ARR, revenue, billings, collections, and other key business metrics
• Build scalable reporting systems, forecasts, and analytical frameworks that support Finance, Accounting, Investor Relations, and executive leadership
• Drive data accuracy and completeness across month-end, quarter-end, and year-end close processes alongside Strategic Finance and Accounting teams
• Collaborate with Engineering, Product, GTM Systems, and Financial Systems teams to ensure the completeness and accuracy of financial data
• Conduct deep-dive analyses that inform strategic decisions and uncover opportunities to improve business performance
• Define, measure, and operationalize key financial and operational metrics
• Design and implement durable data solutions that balance immediate stakeholder needs with long-term scalability
• Serve as a trusted thought partner to Finance leaders, helping guide reporting, forecasting, and decision-making across the business
Qualifications:
Required:
• 3+ years of experience in Data Science, Analytics, Finance, Financial Systems, Data Engineering, or a related field
• Advanced SQL skills and strong proficiency in Python or a similar programming language
• Experience supporting Finance, Accounting, Strategic Finance, FP&A, Investor Relations, or other finance-focused stakeholders
• Demonstrated ability to translate complex data into clear, actionable business insights for non-technical stakeholders
• Experience working independently and driving projects from ambiguity to execution
Preferred:
• Experience with SaaS, subscription-based, usage-based, or consumption-based business models
• Knowledge of accounting concepts and revenue recognition principles (ASC 606)
• Experience with modern analytics and data engineering tools such as DBT, Snowflake, Git, Spark, Presto, or similar technologies
• Experience supporting IPO readiness, public company reporting, SOX controls, audits, or other major corporate milestones
• Background in Strategic Finance, FP&A, Accounting, Investment Banking, Consulting, or related fields
Company:
Figma is a collaborative design tool that enables teams to create, prototype, and test digital products on one platform. Founded in 2012, the company is headquartered in San Francisco, USA, with a team of 1001-5000 employees. The company is currently Late Stage.