Senior AI & Business Analytics Engineer

Job description
Ideal Candidate Profile A hands-on practitioner who has successfully deployed end-to-end AI solutions into production, combining machine learning, cloud engineering, data pipelines, and AI agents. Examples may include pricing propensity models, personalized loan offers, recommendation engines, customer next-best-action solutions, campaign optimization, or revenue growth initiatives.
Key Responsibilities
Business Analytics & Machine Learning
Design and deploy predictive models supporting customer growth, acquisition, retention, and revenue generation.
Build pricing, propensity, recommendation, personalization, and customer segmentation models.
Develop analytics solutions that improve commercial performance across customer journeys.
Work closely with business stakeholders to identify, prioritize, and deliver high-impact analytics opportunities.
AI Agents & Personalization
Design and deploy AI agents supporting customer engagement and decision intelligence.
Leverage Generative AI technologies to improve personalization and customer experience.
Build solutions for
Personalized loan offers
Pricing propensity models
Product recommendation engines
Customer next-best-action solutions
Campaign optimization and targeting
Revenue growth and customer engagement initiatives
Data Engineering & Platform Development
Design and develop ETL/ELT pipelines supporting advanced analytics and AI use cases.
Build DAG-based orchestration and automation workflows.
Ensure reliable access to high-quality data across analytical platforms.
Cloud & AI Platform Engineering
Deploy and manage AI/ML workloads on cloud platforms.
Implement MLOps capabilities and continuous delivery practices.
Support scalable and secure AI platform operations.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related disciplines.
5+ years of experience in Data Science, Machine Learning, AI Engineering, or Advanced Analytics.
Proven experience building and deploying machine learning models into production environments.
Strong Python programming skills and experience with modern AI/ML frameworks.
Experience developing ETL/ELT pipelines and data processing solutions.
Experience with DAG orchestration and workflow automation.
Cloud experience (AWS preferred).
Experience deploying AI/ML solutions and AI agents in production environments.
Practical experience with Generative AI, LLMs, AI Agents, and AI-assisted workflows.
Strong business acumen and ability to translate analytical solutions into measurable business outcomes.
Preferred Qualifications
Banking, fintech, digital banking, or financial services experience.
Experience building
Pricing propensity models
Recommendation engines
Personalization platforms
Customer segmentation solutions
Revenue optimization initiatives
Experience deploying production-grade AI agents.
Demonstrated ability to quantify business impact through revenue growth, customer engagement, conversion improvement, or operational efficiency gains.
(Note: Due to the high volume of applications we receive, we are unable to respond to every candidate individually. If you have not received a response from GFT regarding your application within 10 workdays, please consider that we have decided to proceed with other candidates. We truly appreciate your interest in GFT and thank you for your understanding)