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Fintech Data Science Jobs in Florida (NOW HIRING)

Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related ... Experience in financial services, wealth management, fintech, or another regulated industry is ...

Our client is a well-funded Web3 fintech startup redefining the future of real-time financial ... Collaborate with smart contract developers, frontend engineers, and data scientists to ship ...

Lead Elixir Platform Engineer

Miami, FL · Remote

$170K - $250K/yr

Our client is a well-funded Web3 fintech startup redefining the future of real-time financial ... Collaborate with smart contract developers, frontend engineers, and data scientists to ship ...

Our client is a well-funded Web3 fintech startup redefining the future of real-time financial ... data scientists to ship features end-to-end. The Tech Stack You'll be working with bleeding-edge ...

Our client is a well-funded Web3 fintech startup redefining the future of real-time financial ... data scientists to ship features end-to-end. The Tech Stack You'll be working with bleeding-edge ...

Azure DevOps Engineer

Miami, FL · On-site

$50.50 - $69/hr

QF Analytics LLC is a fintech company that develops and supports one of the world's fastest-growing ... Responsibilities Interface with data scientist, front-end developers, and dB administrators to ...

Engineering - FinTech Location : Plantation, FL, USA Employment Type : Full-time Key ... Integrate real-time data processing solutions, such as Kafka or Hadoop, to handle high-throughput ...

Engineering - FinTech Location : Plantation, FL, USA Employment Type : Full-time Key ... Integrate real-time data processing solutions, such as Kafka or Hadoop, to handle high-throughput ...

Showing results 41-60

Fintech Data Science information

See Florida salary details

$28K

$91.7K

$146.8K

How much do fintech data science jobs pay per year?

As of Sep 12, 2026, the average yearly pay for fintech data science in Florida is $91,721.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,600.00 and $101,600.00 per year, depending on experience, location, and employer.

What is a fintech data scientist?

A Fintech Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to solve problems and create value within the financial technology (fintech) industry. They work with large amounts of financial data to develop predictive models, detect fraud, assess risk, and optimize financial products or services. Their expertise combines knowledge of finance, programming, and advanced analytics to help fintech companies make data-driven decisions and innovate in areas such as payments, lending, and investment. Fintech Data Scientists often collaborate with engineers, product managers, and business stakeholders to deliver actionable insights that drive business growth.

What are the key skills and qualifications needed to thrive as a fintech data scientist?

To thrive as a Fintech Data Scientist, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, mathematics, or a related field). Familiarity with tools such as Python, R, SQL, cloud computing platforms, and experience with financial data modeling or relevant certifications are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills that set top professionals apart. These skills and qualities are vital for extracting actionable insights from complex financial data, driving innovation, and ensuring regulatory compliance in the fast-evolving fintech industry.

How do fintech data scientists typically collaborate with product and engineering teams to develop new financial products?

In fintech, data scientists often work closely with product managers and engineering teams throughout the lifecycle of a financial product. They analyze user data and market trends to provide actionable insights during the product design phase, and collaborate with engineers to implement machine learning models into the product infrastructure. Regular cross-functional meetings and agile workflows are common, allowing data scientists to iterate on models based on feedback and evolving requirements. This collaborative environment ensures that data-driven solutions are robust, scalable, and aligned with business goals.

What is the difference between Fintech Data Science vs Fintech Data Analyst?

AspectFintech Data ScienceFintech Data Analyst
Required SkillsAdvanced statistical, programming, and machine learning skillsData interpretation, reporting, and basic analytics
CertificationsData Science certifications, programming coursesData analysis or business intelligence certifications
Work EnvironmentDeveloping models, algorithms, and predictive analyticsData reporting, dashboards, and data cleaning
Industry UsageCreating predictive models for risk, fraud detection, and customer insightsGenerating reports, supporting decision-making with data

Fintech Data Science involves building complex models and applying machine learning techniques, requiring advanced skills and certifications. Fintech Data Analysts focus on interpreting data, creating reports, and supporting business decisions with less technical complexity. Both roles are essential in the fintech industry but differ in technical depth and responsibilities.

Is data science good for fintech?

Data science is highly valuable in fintech, as it enables the development of algorithms for risk assessment, fraud detection, and personalized financial services. Fintech companies often rely on data analysis, machine learning, and statistical modeling to improve decision-making and customer experience. Skills in programming, data manipulation, and financial knowledge are essential for data scientists in this field.

Is fintech data science a high paying career?

Fintech data science is generally a high-paying career due to the demand for advanced analytics and machine learning skills in financial technology companies. Salaries often depend on experience, education, and technical expertise in tools like Python, R, and SQL, with senior roles earning significantly more. The field offers competitive compensation compared to many other data science roles across industries.
Infographic showing various Fintech Data Science job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $91,721 per year, or $44.1 per hour.

AI Solutions Engineer

Fort Lauderdale, FL • On-site

Sound Income Group LLC
Finance and Insurance • 51 - 200 employees

Other

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago


Job description

About this position

Description:

POSITION: AI Solutions Engineer

Location & Hours: Onsite | M-F 8:30-5:00pm

FLSA Classification: Exempt

Who We Are

At Sound Income Group, our mission is to help independent financial professionals and their clients thrive, especially those approaching or in retirement. We provide a full suite of resources across financial education, investment strategies, marketing, and practice management to support long-term success.

Position Summary

The AI Solutions Engineer will lead the development and implementation of artificial intelligence, machine learning, and automation solutions across Sound Income Group. As a new add-to-staff position, this individual will have significant ownership in evaluating current processes, identifying opportunities to improve efficiency and cost effectiveness, and building solutions that deliver measurable business results.

This role requires a hands‑on, highly autonomous engineer with broad expertise across machine learning, generative AI, data engineering, and business‑process automation. The AI Solutions Engineer will partner with leaders across Marketing, Business Development, Recruiting, Sales, Coaching, Advisor Support, and Operations to understand departmental needs and determine which processes can be enhanced through AI and which require continued human oversight.

Key Responsibilities
  • Evaluate workflows, systems, and data across departments to identify opportunities for AI, machine learning, and automation.
  • Develop and maintain a prioritized AI roadmap based on business impact, feasibility, efficiency, cost-effectiveness, and risk.
  • Design, build, test, deploy, and maintain production-ready AI and machine‑learning solutions.
  • Develop department‑specific AI assistants, agents, and automation tools that improve productivity and support business needs.
  • Build solutions supporting lead generation, lead qualification, lead routing, recruiting, marketing, business development, and back‑office operations.
  • Create and maintain reliable data pipelines and integrations across internal systems, databases, APIs, and third‑party platforms.
  • Partner with department leaders and subject‑matter experts to understand business challenges and translate them into practical technical solutions.
  • Determine whether each business need is best addressed through generative AI, machine learning, rules‑based automation, third‑party technology, or a human‑led process.
  • Develop prototypes, gather user feedback, and convert validated concepts into secure, scalable, and maintainable solutions.
  • Establish benchmarks and reporting to measure solution accuracy, adoption, efficiency, cost savings, lead conversion, and overall business impact.
  • Implement appropriate security, privacy, permissions, human‑review controls, and governance standards for AI solutions.
  • Evaluate AI platforms, vendors, models, and emerging technologies and make recommendations regarding scalability, security, business fit, and cost.
  • Document technical requirements, architecture, data flows, procedures, and ongoing maintenance needs.
  • Educate employees and leaders on AI capabilities, limitations, responsible use, and adoption best practices.
  • Operate with a high degree of independence and take ownership of projects from initial discovery through implementation and ongoing optimization.
Requirements Must-Have Qualifications

Background and Education:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related field; equivalent experience may be considered.
  • Minimum of four years of experience across AI engineering, machine learning, and data engineering.
  • Proven experience owning AI or machine‑learning solutions from discovery and development through production deployment and optimization.
  • Strong proficiency in Python, SQL, data pipelines, APIs, and system integrations.
  • Ability to translate complex business needs into practical solutions and operate independently with minimal instruction.

Preferred Experience:

  • Experience with Databricks, Snowflake, cloud infrastructure, and MLOps or LLMOps.
  • Experience building generative AI applications, AI agents, workflow automations, RAG solutions, or internal assistants.
  • Knowledge of AI security, privacy, governance, permissions, and human‑review controls.
  • Experience supporting enterprise‑wide AI initiatives, evaluating vendors, and making build‑versus‑buy recommendations.
  • Experience in financial services, wealth management, fintech, or another regulated industry is preferred.
Physical & Work Environment Requirements
  • Ability to work for extended periods at a desk using a computer.
  • Ability to lift up to 10 pounds if/when necessary.
  • Routine use of telephone and email.
  • Office‑based role with potential travel to conferences, events, and satellite offices as needed.
Benefits

We’re proud to offer a comprehensive benefits package that supports your professional and personal well‑being, including:

  • 100% employer‑covered medical benefits and HRA account
  • Dental & vision plans
  • PTO + 10 NYSE company holidays per year
  • 401K with company match program
  • Free onsite parking
  • Company‑provided laptop and required technology
  • Access to an on‑site gym (free of charge)
  • Weekly carwash (at an additional cost)

Sound Income Group is an E-Verify employer.

Sound Income Group is an equal opportunity employer that complies with all applicable federal, state, and local laws, rules and regulations. It is our policy to employ and promote qualified candidates without discrimination on the basis of race, color, sex, age, origin, sexual orientation, marital status, disability or any other characteristic protected by law. Our hiring decisions are based solely on merit, qualifications and business needs.

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