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Weekend Data Analyst Fintech Jobs (NOW HIRING)

Fintech

Distributor Data Analyst

Tampa, FL · Hybrid

Join Fintech in Tampa, FL as a Distributor Data Analyst! The Distributor Data Analyst partners with the Distributor Strategy Team to increase the percentage of Fintech retail customers with targeted ...

Fintech

Distributor Data Analyst

Tampa, FL · On-site

Join Fintech in Tampa, FL as a Distributor Data Analyst! The Distributor Data Analyst partners with the Distributor Strategy Team to increase the percentage of Fintech retail customers with targeted ...

Fintech Brand

Distributor Data Analyst

Tampa, FL · On-site

Martin Luther King Jr. Blvd. Suite 200 Tampa, FL 33607, USA Join Fintech in Tampa, FL as a Distributor Data Analyst! The Distributor Data Analyst partners with the Distributor Strategy Team to ...

Apex Fintech Solutions

Data Analyst

Chicago, IL · Hybrid

$75K - $94K/yr

WHO WE ARE Apex Fintech Solutions (Apex) powers innovation and the future of digital wealth ... Data Analyst Location : 141 W. Jackson Blvd., Suite 500, Chicago, IL 60604 Responsibilities

1 point system

Data Analyst

Sunnyvale, CA · On-site

Master's degree in data science, Statistics, Computer Science, Economics, or a related field. * 4+ years of industry experience in Payments, Risk, FinTech, or Marketplace Analytics. * Proven ability ...

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How much do weekend data analyst fintech jobs pay per year?

As of Sep 12, 2026, the average yearly pay for weekend data analyst fintech in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Analyst Fintech vs Weekend Data Analyst Banking?

AspectWeekend Data Analyst FintechWeekend Data Analyst Banking
Required CredentialsBachelor's in Data Science, Finance, or related field; familiarity with fintech toolsBachelor's in Finance, Economics, or related; knowledge of banking systems
Work EnvironmentStartups, online platforms, flexible hoursTraditional bank branches, financial institutions, similar flexible weekend roles
Employer & Industry UsageFintech companies, online lenders, digital payment firmsCommercial banks, retail banking, financial services

The main difference between Weekend Data Analyst Fintech and Weekend Data Analyst Banking lies in the industry focus and work environment. Fintech roles are often in innovative, digital-focused companies requiring familiarity with new financial technologies, while banking roles are within traditional financial institutions emphasizing banking systems and regulations. Both roles typically require similar data analysis skills but cater to different sectors within finance.

What cities are hiring for Weekend Data Analyst Fintech jobs?

Cities with the most Weekend Data Analyst Fintech job openings:

What are the most commonly searched types of Data Analyst Fintech jobs?

The most popular types of Data Analyst Fintech jobs are:

What states have the most Weekend Data Analyst Fintech jobs?

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Weekend Data Analyst Fintech jobs near you
Infographic showing various Weekend Data Analyst Fintech job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Fraud & Risk Data Analyst Fintech & Data Insights *** Direct End Client ***

Mountain View, CA • On-site

Projas Technologies, LLC
1 - 10 employees
Learn more about Projas Technologies, LLCexternal

Other

Re-posted 15 days ago

Job description

Staff Fraud & Risk Analyst Fintech & Data Insights

As a Fraud & Risk Data Analyst, you ll work at the intersection of analytics, compliance, and product innovation. This role is part of a dynamic Risk Insights and Experimentation team that influences billions of dollars in transactions annually. You ll partner with cross-functional teams to uncover insights, design experiments, and shape strategies that drive secure, scalable growth.

Domain expertise in Security, Risk & Fraud in Fintech space (consumer Lending, Fraud & Risk Policy, Compliance, Marketing, Product, Finance is required)

Key Responsibilities:
  • Deliver clear, persuasive insights to senior leadership through data storytelling and executive-ready reports.
  • Build intuitive dashboards and visualizations that guide strategic and operational decisions.
  • Design and interpret A/B tests to optimize product performance and risk strategies.
  • Collaborate with product, compliance, finance, and data science teams to define scalable analytics frameworks.
  • Analyze large-scale transactional and behavioral data to detect trends, anomalies, and fraud patterns.
  • Evaluate compliance effectiveness and recommend improvements to onboarding and remediation flows.
  • Translate ambiguous business questions into structured analytical approaches using SQL, Python, and visualization tools.
  • Investigate root causes of performance gaps and propose timely corrective actions.
  • Maintain clean, reliable data pipelines and address data quality issues proactively.
Qualifications:
  • 6+ years in analytics, data science, or decision strategy roles, ideally in Financial Services or Fintech.
  • Advanced SQL skills and working knowledge of Python for data manipulation and automation.
  • Experience with data visualization tools (Tableau, Quicksight, Qlik) and dashboard development.
  • Strong understanding of A/B testing principles and experimental design.
  • Proven ability to influence decisions through data-driven recommendations.
  • Excellent communication skills for translating complex data into actionable insights.
  • Bachelor s degree in a quantitative field (Economics, Math, Science) or equivalent experience.

fraud analyst, risk analyst, fintech analytics, SQL, Python, A/B testing, data visualization, Tableau, Quicksight, Qlik, compliance analytics, risk management, dashboard development, data science, financial services, experimentation, policy analytics, fraud detection, risk strategy, KPIs, OKRs, data storytelling

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