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)

Senior AI & Business Analytics Engineer