Data Scientist

FIS Global is hiring a Data Scientist to help build and scale data-driven exploratory analysis, predictive models, and AI solutions across financial services business areas. This onsite role in Atlanta, GA focuses on supporting the full machine learning lifecycle and turning analytical results into practical, product-ready recommendations.

You will work on advanced analytics spanning model development through monitoring, with an emphasis on measurable business impact in payments and broader financial services.

What you’ll do

• Participate in the end-to-end design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions.
• Use data structures and algorithms to analyze, prepare, and assemble datasets from standard and novel data sources for analytical solutions.
• Apply machine learning, predictive analytics, NLP, and emerging AI approaches such as GenAI and agentic techniques to address complex problems in the payments and financial services ecosystem.
• Design and run experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
• Establish and promote best practices across feature engineering, experimentation, model governance, and MLOps within the organization.
• Stay current with industry trends in machine learning, AI, generative AI, and financial services analytics, and share relevant innovations with the team.

What you’ll bring

• Master’s degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative field.
• 1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions in Payments, Banking, or Financial Services.
• Strong proficiency in Python and SQL, with experience using big data tools such as Spark and PySpark as a plus.
• Hands-on experience with data wrangling, feature engineering, and model development using Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, or Plotly.
• Proven experience building and deploying machine learning models in production or near-production settings.
• Proficiency with data visualization and business intelligence tools, such as Tableau or equivalent.
• Strong analytical thinking and problem-solving skills, including the ability to translate ambiguous business questions into rigorous analytical frameworks.
• Ability to collaborate with product, engineering, and business stakeholders.

Technologies you may work with

• Python, SQL, Spark, PySpark
• Pandas, NumPy, scikit-learn
• Matplotlib, Seaborn, Plotly
• Tableau
• NLP, GenAI, Agentic
• MLflow, Model Registry, MLOps
• Databricks (including Databricks platform), AWS
• Transformer Models

Benefits

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

Nice to have

• Experience specifically 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 in AWS environments.
• Familiarity with emerging advancements in Transformer Models and agentic AI.
• Knowledge of model governance, regulatory compliance, and MLOps best practices in regulated financial services environments.