Data Scientist Lead
Atlanta, GAFull-timePosted 1 day agoStill listed today
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Requirements
Credentials this posting asks for.
Job overview
The Data Scientist Lead develops and deploys exploratory analysis, predictive models, and AI solutions for business problems across financial services, particularly in risk, fraud, marketing, and portfolio management. The role leads solutions through the machine learning lifecycle and turns results into product recommendations. It also advances data science practices and communicates analytical findings to internal and external audiences.
Skills & qualifications
Skills
Qualifications
Full job description
Position Type
Full time
Type Of Hire
Experienced (relevant combo of work and education)
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.
Current and future sponsorship are not available for this position.
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
- 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, 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
- Communicate complex analytical findings through compelling storytelling, executive-ready presentations, dashboards, visualizations and self-service analytics tools. that drive informed decision-making
- 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
- 5+ 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
- Working 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.
Sourcing Model
Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.
#pridepass
How this job compares
Set against the 5,012 open Data Scientist jobs on Olive Jobs, counted November 6, 2026.
- Pay
- This postingNot listed
- Georgia median$119–199K/yr69 salary ranges
- US median$55–75/hr139 hourly ranges
- Openings
- Olive Jobs lists 142 open Data Scientist jobs in Georgia and 5,012 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most in Georgia
- Home Depot49 open
- Deloitte12 open
- The Hertz Corporation5 open
- Experience
- This posting asks for at least 5 years of experience; Data Scientist postings that state a minimum ask for 5 years at the median (4,316 postings).
- Education
- This posting asks for a master's degree; 612 of the 5,012 open Data Scientist jobs (12%) ask for a master's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 6, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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