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Fidelity National Information Services

Global provider of financial technology solutions

Data Scientist Senior Lead

Applied Machine LearningPosted on Nov 12
Full-timeAtlanta, GA, USANo salary listedIn-person

About the Job

Requirements

  • A master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • At least 7 years of professional experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the payments, banking, or financial services industry.
  • Demonstrated deep technical leadership in solution design and data and model architecture, actively leading cross-functional teams to execute key deliverables.
  • Strong proficiency in Python and SQL.
  • 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 pipelines in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools such as Tableau or equivalent.
  • Strong analytical thinking and problem-solving skills, with the ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Responsibilities

  • Lead 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, assemble datasets from standard and novel data sources, and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing, and emerging AI techniques, including generative AI and agentic AI, 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.
  • Communicate complex analytical findings through storytelling, executive-ready presentations, dashboards, visualizations, and self-service analytics tools to drive informed decision-making.
  • Stay current on industry trends in machine learning, AI, generative AI, and financial services analytics, and bring relevant innovations to the team.

Desired Qualifications

  • Experience with big data technologies such as Spark and PySpark.
  • Ability to convert ambiguous, open-ended questions into structured problem-solving approaches leveraging data science and AI.
  • High competence in leading teams through complex model design and developing solutions from concept and ideation to market-ready products.
  • 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.
  • Working familiarity with emerging advancements in building real-world solutions leveraging Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

About the Company

Fidelity National Information Services

Global provider of financial technology solutions

Fidelity National Information Services (FIS) provides technology solutions for financial institutions and businesses worldwide, covering core banking, digital banking, and payment processing, as well as trading, risk management, and securities processing for capital markets. Its products are integrated software platforms and services that clients embed to process transactions, manage risk, and support digital channels, with revenue from software licenses, maintenance, and per-transaction fees. It differentiates itself by offering an end-to-end suite across banking, payments, and capital markets with a global client base, serving both large banks and smaller institutions in one integrated package. Its goal is to help financial institutions navigate digital transformation and operate more efficiently through reliable, scalable technology platforms and services.

Company size
1-10
Company stage
IPO
Headquarters
Jacksonville, FL
Founded
1968

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