{"id":4212517,"url":"https://alion.io/job/fis-data-scientist-senior-lead","title":"Data Scientist Senior Lead","company":{"id":4808,"name":"FIS","domain":"fisglobal.com","url":"https://alion.io/company/fis","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":91,"ghost_share":0.011,"stale_share":0.604,"repost_share":0.033,"time_to_fill_p50_days":27,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Atlanta, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Plotly","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Seaborn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false},{"name":"AI Agents","optional":true},{"name":"AWS","optional":true},{"name":"Databricks","optional":true},{"name":"MLFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-11-12T00:00:00Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-13T01:30:48Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Job Description\nInnovation isn’t just what we do; it’s how we work. At FIS, you’ll collaborate with talented people across the globe to create solutions that shape the way the world pays, banks and invests. If you’re ready to grow your career while making a meaningful impact, we’d love to meet you.\nCurrent and future sponsorship are not available for this position.\nLocation: Atlanta, GA\nAbout the role:\nAs 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.\nYour key responsibilities:\nLead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.\nLeverage 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.\nApply 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.\nDesign and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.\nEstablish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.\nCommunicate complex analytical findings through compelling storytelling, executive-ready presentations, dashboards, visualizations and self-service analytics tools. that drive informed decision-making.\nStay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.\nWhat you bring:\nRequired qualifications:\nMaster's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.\nAt 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.\nDemonstrated deep technical leadership in solution design, data and model architecture, actively leading cross-functional teams to execute on key deliverables.\nStrong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.\nHands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.\nDemonstrated experience building and deploying machine learning pipelines in a production or near-production environment.\nProficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).\nStrong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.\nAbility to work collaboratively across product, engineering, and business teams.\nPreferred qualifications:\nAbility to convert ambiguous, open ended questions into structured problem-solving approaches leveraging data science and AI.\nHigh competence in leading teams through complex model design and development of solutions from concept and ideation to market-ready products.\nExperience within the Payments, Banking, or Financial Services industry.\nHands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.\nExperience deploying cloud-native machine learning solutions, particularly within AWS environments.\nWorking familiarity with emerging advancements in building real-world solutions leveraging Transformer Models and Agentic AI technologies.\nKnowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.\nWhat we offer you:\nAt FIS, your career journey is yours to shape. We provide the tools, experiences and support to help you reach what's next.\nHere’s what else we offer:\nOpportunities to make an impact in fintech\nInternal career growth opportunities\nPersonal and professional learning\nInclusive, diverse work environment\nResources to give back to your community\nPrivacy Statement\nFIS 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.\nEEOC Statement\nFIS 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\nFor 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.\nSourcing Model\nRecruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. 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