12 MONTHS CONTRACT

We are looking for an experienced Senior Data Engineer / Data Scientist with strong AI/ML expertise to join our dynamic team in the Banking/FinTech space. This role is ideal for someone who thrives in data-driven environments, enjoys solving complex problems, and has experience delivering production-ready AI/ML solutions.

Minimum Requirements

Experience

5+ years relevant experience as a Data Engineer/Data Scientist.

4–6+ years applied data science experience.

2+ years owning and deploying production AI/ML models.

3+ years’ experience in FinTech, Banking, or Financial Services.

Proven delivery of automated decisioning models (e.g., recommendation, forecasting, fraud, propensity) with measurable business impact.

Hands-on experience in data engineering in financial services.

Strong understanding of enterprise-scale data systems.

Experience working in Agile/DevOps environments.

GitHub/GitLab for CI/CD pipelines and collaborative development.

Experience improving CI/CD pipelines to support “develop once, deploy many” frameworks using container repositories.

Proven experience with:

Python (essential), SAS, R, or Scala

Big Data tech: Hadoop, Spark, MapReduce, PIG, Hive

Databases: Postgres, Oracle, MongoDB, MSSQL

Ability to work with software-agnostic data tools for querying and reporting.

Experience working in medium-to-large scale organizations.

Experience in eCommerce or electronic payments (advantageous).

Experience working across global regions with an understanding of regulatory and infrastructure challenges (advantageous).

Qualifications

Bachelor’s degree in Computer Science, Mathematics, Statistics, Data Science or related field (required).

Master's degree in Data Science / AI/ML / Statistics (preferred).

MBA or equivalent master’s qualification (advantageous).

Technical Skills

Strong capability in cloud + on-premise data engineering (Azure, AWS, or GCP).

Proficiency with CI/CD orchestration, automation and repository management.

Highly skilled in Python, Spark (Scala), R and Jupyter Notebook for advanced analytics & machine learning.

Strong analytical and storytelling abilities using visualization tools:

Power BI, Data Studio, Kibana, etc.

Advanced working knowledge of Hadoop, Spark, and Big Data ecosystems.