Senior Applied Data Scientist
First seen by Alion on Sep 17, 2026. FCI CCM scores B on the Alion truth index.
Join the Legacy of Innovation with FCI-CCM :
Backed by a legacy of innovation since 1959, FCI has built over six decades of expertise in communications, continuously evolving to meet changing business and technology needs. By combining deep domain knowledge with innovation, FCI has consistently delivered enterprise-grade communication solutions that help organizations adapt to an increasingly digital world.
Today, FCI continues that legacy through its flagship platform, VARTA, an Insights-Led Customer Communications Platform that empowers organizations to unify customer intelligence, communication workflows, behavioural signals, and engagement orchestration to deliver intelligent, personalized, and real-time customer experiences.
Broad Function :
FCI is building advanced AI capabilities to help banks convert transactions and behavioral signals into relevant customer engagement and measurable growth. The initial focus will be on credit cards, with a product designed for reuse across multiple banks and deployment within bank-controlled environments.
The Senior Applied Data Scientist / ML Lead will act as FCI's hands-on analytical lead and will work closely with our banking/data-science co-development partner, along with internal Product, Architecture and Engineering teams. The role will involve building, challenging and improving machine learning models while creating a lasting analytical capability within FCI beyond the initial engagement.
Roles and Responsibilities :
- Translate banking growth hypotheses into meaningful features, labels, models and measurable experiments in collaboration with the Product team and banking SMEs.
- Build and evaluate approaches for transaction classification, behavioural segmentation, recommendation and ranking, and customer propensity and targeting.
- Own the complete model evaluation framework, including time-based holdouts, leakage prevention, class imbalance handling, model calibration, segment-level error analysis, treatment/control evaluation, and separation of predictive accuracy from incremental business impact.
- Write production-quality Python, tests and reproducible training/evaluation pipelines.
- Work closely with Data Engineering and MLOps teams on model deployment, monitoring, retraining, rollback, automated validation, and CI/CD for ML workflows.
- Work hands-on with FCI's banking/data-science co-development partner to reproduce results, challenge assumptions, and document model logic.
- Maintain a clean separation between reusable core model code and bank-specific components to support configurable onboarding.
- Design ML solutions for bank-controlled environments, including on-premises and private-cloud deployments.
- Work within bank security controls and maintain proper model provenance, documentation and auditability.
Success in First 6-9 Months :
- First 90 Days : Reproduce partner baseline models, establish evaluation methodology, and deliver at least one independently implemented analytical improvement.
- By Month 6 : Operate and improve agreed model workflows, demonstrate reproducibility, and explain model logic to stakeholders.
- By Month 9 : Lead a controlled model enhancement, enable at least one additional FCI colleague to execute critical ML workflows, and support reuse for a second banking client.
Total Experience : 5-10 years
Skills
Data Science, Data Scientist, Machine Learning, Python, MLOps, System Configuration, Solution Design, Cloud