Data Scientist

FIS; Jacksonville (FL); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Learning opportunities

Collaborative culture

Community impact

Competitive benefits

Job summary

FIS seeks a data scientist to deploy data-driven analytics and AI solutions across risk, fraud, marketing, and portfolio management in financial services. Convert findings into actionable product recommendations for internal and external stakeholders.

Join a collaborative Data Science team, work with Python/SQL, leverage Spark and other big data tools, and contribute to ML, NLP, and GenAI initiatives with strong governance and ML lifecycle practices.

Qualifications

• Master’s degree or higher in a quantitative field.
• 1–3 years in end-to-end ML / data science in financial services.
• Strong Python and SQL skills; experience with big data tech.

Responsibilities

• Design, develop, validate, deploy, and monitor advanced analytics and ML solutions.
• Prepare data from multiple sources and build end-to-end analytical pipelines.
• Apply NLP and GenAI techniques to business problems in payments and finance.
• Run experiments, assess hypotheses, and support product decisions.
• Promote best practices in MLOps, governance, and model lifecycle.

Skills

Python

SQL

Data wrangling

Feature engineering

Model deployment

Problem solving

Collaboration

Education

Master’s degree

Tools

Spark

PySpark

Pandas

NumPy

Scikit-learn

Matplotlib

Seaborn

Plotly

Tableau

Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you’ll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you’ll be doing

• Participate in the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
• Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
• Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
• Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
• Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
• Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring

• Master’s degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
• 1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
• Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
• Hands‑on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
• Demonstrated experience building and deploying machine learning models in a production or near-production environment.
• Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
• Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
• Ability to work collaboratively across product, engineering, and business teams.

Nice to have

• Experience within the Payments, Banking, or Financial Services industry.
• Hands‑on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
• Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
• Familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
• Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you

A career at FIS is more than just a job. It’s the chance to shape the future of fintech. At FIS, we offer you:

• A voice in the future of fintech
• Always‑on learning and development
• Collaborative work environment
• Opportunities to give back
• Competitive salary and benefits

Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here

For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.