Data Scientist Sr Lead

FIS Management Services LLC; United States; On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive salary and benefits package

Collaborative work environment with continuous learning opportunities

Opportunities to give back to the community

Job summary

FIS Management Services LLC is seeking a senior Data Scientist to spearhead advanced analytics and AI solutions in the payments and financial services industry. The role involves leading projects that drive measurable business outcomes through machine learning and big data analysis.

The ideal candidate will possess a Master’s degree, along with significant experience in machine learning applications and programming skills in Python and SQL. Responsibilities include developing AI solutions, analyzing datasets, and mentoring junior team members, contributing to innovative business strategies.

Qualifications

• 5+ years of experience in machine learning and predictive analytics.
• Proficiency in Python and SQL.
• Experience with data visualization tools like Tableau.

Responsibilities

• Lead design and deployment of machine learning solutions.
• Analyze large datasets for insights and trends.
• Communicate findings through presentations and dashboards.

Skills

Machine learning

Data analysis

Python

SQL

Tableau

Natural Language Processing

MLOps

Statistics

Education

Master's degree in a quantitative discipline

Tools

Databricks

Spark

Scikit-learn

Pandas

Job description

Job Overview

FIS seeks a senior Data Scientist to lead advanced analytics and AI solutions within the payments and financial services domain. The role focuses on the machine learning lifecycle, experimentation, and business impact across risk, fraud, marketing, and portfolio management.

Responsibilities

• Lead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
• Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
• Analyze and mine large-scale structured and unstructured datasets to uncover actionable insights, identify emerging trends, and support strategic decision-making.
• Develop, test, and operationalize analytical and machine learning solutions for internal stakeholders and external clients, ensuring scalability, reliability, and business impact.
• Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques to solve complex business problems across the payments and financial services ecosystem.
• Lead independent quantitative research initiatives, leveraging multiple data sources to generate innovative insights and identify new business opportunities.
• Partner with product, engineering, business, and executive stakeholders to translate business objectives into data-driven solutions and measurable outcomes.
• Communicate complex analytical findings through storytelling, executive‑ready presentations, dashboards, and visualizations that drive informed decision-making.
• Design and develop automated dashboards, performance scorecards, and self-service analytics solutions to monitor key business metrics, customer behaviors, model performance, and operational health.
• Establish and promote best practices in data science, machine learning, experimentation, model governance, and MLOps throughout the organization.
• Lead proof-of-concept initiatives to evaluate emerging technologies, machine learning techniques, and generative AI capabilities, translating successful pilots into production-ready solutions.
• Drive model lifecycle management, including feature engineering, model training, validation, deployment, monitoring, retraining, and performance optimization.
• Mentor and develop junior data scientists, fostering a culture of technical excellence, innovation, collaboration, and continuous learning.
• Provide technical leadership and guidance on analytical methodologies, model selection, data quality, and solution architecture.
• Collaborate with data engineering teams to define data requirements, optimize data pipelines, and ensure availability of high-quality data for analytics and machine learning initiatives.
• Ensure adherence to regulatory, security, compliance, and model governance standards within a highly regulated financial services environment.
• Stay current on industry trends and advancements in machine learning, artificial intelligence, generative AI, cloud technologies, and financial services analytics.
• Contribute to strategic planning by identifying opportunities where advanced analytics and AI can create competitive advantage and business value.
• Perform other duties and responsibilities as assigned.

Minimum Qualifications

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or another 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 data science programming languages and big data technologies, including Python, SQL, Spark, PySpark, R, and Hadoop.
• Extensive experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Plotly, Matplotlib, and Seaborn.
• Advanced expertise in data visualization and business intelligence platforms, including Tableau.
• Hands‑on experience with the Databricks platform, including MLflow, AutoML, Model Registry, collaborative notebooks, and MLOps workflows.
• Demonstrated ability to identify innovative business opportunities, develop proof-of-concept projects, and translate successful pilots into scalable solutions.
• Strong experience building and deploying machine learning models, including classification, clustering, and predictive models such as Random Forest, XGBoost, Gradient Boosting, and K‑Means.
• Experience applying Natural Language Processing (NLP) techniques to solve business challenges.
• Proven ability to communicate complex analytical concepts and insights to both technical and non-technical stakeholders.

Preferred Qualifications

• Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
• Experience designing and deploying cloud-native data science and machine learning solutions within AWS environments.
• Demonstrated success in productizing machine learning models and analytics solutions for enterprise-scale production environments.
• Experience leading the deployment, monitoring, governance, and lifecycle management of production-grade machine learning applications.
• Knowledge of generative AI technologies, including large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and related frameworks.
• Experience mentoring junior data scientists and providing technical leadership across complex analytics initiatives.
• Familiarity with modern MLOps practices and model governance within regulated financial services environments.

Benefits

• Competitive salary and benefits package.
• Collaborative work environment with continuous learning opportunities.
• Opportunities to give back to the community.
• Voice in shaping the future of fintech.
• Always-on learning and development resources.
• Collaborative work environment.

Legal 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.