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Data Analytics Finance Jobs (NOW HIRING)

Anthropic

Analytics, Finance & Strategy

San Francisco, CA · On-site

$270K - $320K/yr

This is a role spanning data analysis, business intelligence and analytics engineering, partnering ... Partner with Finance & Strategy teams (Product, Compute, GTM, and Corporate) to answer their most ...

Vizient

Data & Financial Analytics Lead

Englewood, CO

$77K - $135K/yr

Relevant degree (e.g., Data Analytics, Finance, Supply Chain, Business, or related discipline) preferred. Advanced degree desired. * 7 or more years of relevant experience required. * Advanced ...

Vizient, Inc.

Data & Financial Analytics Lead

Irving, TX

$77K - $135K/yr

Relevant degree (e.g., Data Analytics, Finance, Supply Chain, Business, or related discipline) preferred. Advanced degree desired 7 or more years of relevant experience required. Advanced proficiency ...

Vizient, Inc.

Data & Financial Analytics Lead

Irving, TX · On-site

$77K - $135K/yr

Relevant degree (e.g., Data Analytics, Finance, Supply Chain, Business, or related discipline) preferred. Advanced degree desired. * 7 or more years of relevant experience required. * Advanced ...

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How much do data analytics finance jobs pay per year?

As of Jun 6, 2026, the average yearly pay for data analytics finance in the United States is $85,459.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $100,500.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by professionals in Data Analytics Finance, and how can they be addressed?

Professionals in Data Analytics Finance often encounter challenges such as integrating data from multiple financial systems, ensuring data accuracy, and communicating insights to non-technical stakeholders. Addressing these challenges involves staying adept with data cleaning methods, collaborating closely with IT and business teams, and developing strong data visualization and storytelling skills. Regular training on emerging analytics tools and fostering open communication within cross-functional teams can also significantly enhance efficiency and impact.

What is Data Analytics in Finance?

Data analytics in finance refers to the process of collecting, processing, and analyzing financial data to make informed business decisions. It involves using statistical tools and software to uncover trends, predict future outcomes, and identify risks or opportunities in financial operations. Professionals in this field help organizations optimize their financial strategies, improve performance, and ensure compliance. Data analytics is increasingly important in finance as it allows companies to gain deeper insights from large volumes of financial data.

What are the key skills and qualifications needed to thrive as a Data Analytics Finance professional, and why are they important?

To thrive as a Data Analytics Finance professional, you need strong quantitative analysis skills, financial acumen, and typically a degree in finance, economics, mathematics, or a related field. Proficiency with data analysis tools such as Excel, SQL, Python, and financial modeling software, as well as certifications like CFA or FRM, are highly beneficial. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and sharing insights with stakeholders. These skills ensure accurate financial analysis, data-driven decision-making, and effective collaboration within finance teams.
More about Data Analytics Finance jobs
What job categories do people searching Data Analytics Finance jobs look for? The top searched job categories for Data Analytics Finance jobs are:
Infographic showing various Data Analytics Finance job openings in the United States as of May 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $85,459 per year, or $41.1 per hour.
Data Analytics - Data Analytics Specialist

Data Analytics - Data Analytics Specialist

CivicMinds, Inc.

San Diego, CA • On-site

Full-time

Posted 22 days ago

Job description

Essential Duties and Responsibilities:
Primary Functions:
  1. Performs monthly end-user data collection, validation, and reconciliation.
  2. Extracts, aggregates, and analyzes data from eClinicalWorks (eCW) and other internal systems.
  3. Develops, maintains, and enhances Tableau dashboards and data visualizations.

Primary Functions: continue
  1. Produces recurring and ad hoc reports for clinical, operational, financial, and grant-related needs.
  2. Ensures data integrity through routine audits, exception reporting, and reconciliation processes.
  3. Standardizes data definitions, report structures, and validation methodologies.
  4. Reviews data for accuracy, identifies trends and variances, and works with appropriate departments to resolve discrepancies.
  5. Prepares data for UDS, HRSA, grant, and other regulatory reporting requirements.
  6. Creates automated and manual reporting tools to improve reporting efficiency and reduce duplication.
  7. Maintains documentation for data sources, report logic, and dashboard development.
  8. Provides technical support to report users in understanding data outputs and dashboard functionality

Qualifications:
Minimum Qualifications:
  1. Three (3) years of experience in healthcare data analytics or data reporting.
  2. Bachelor's degree in business, public health, health informatics, data analytics, finance, economics, or a related field.
  3. Hands-on experience developing Tableau dashboards and data visualizations.
  4. Experience extracting and working with data from eClinicalWorks (eCW).
  5. Advanced Microsoft Excel skills, including pivot tables, complex formulas, and data analysis functions.

Preferred:
  1. Experience in a Federally Qualified Health Center (FQHC) or community health clinic environment.
  2. Experience with UDS, HRSA, or grant-related reporting.
  3. Familiarity with SQL, SPSS, or other statistical/analytical tools.
  4. Experience working with multicultural and underserved populations

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