Role Overview

We are seeking a skilled Data Scientist with strong expertise in advanced analytics, NLP, and cloud-based data platforms. The ideal candidate will work on building scalable data solutions and AI/ML models within a cloud environment, supporting business use cases in the banking/insurance domain.

Required Skills & Experience

4–8 years of experience in Data Science / ML / Data Engineering.
Strong programming skills in Python and SQL.
Hands-on experience with PySpark and distributed data processing.
Experience with Azure cloud services and Databricks (Unity Catalog, Jobs, Pipelines).
Knowledge of NLP, advanced analytics, and machine learning techniques.
Experience with LLMs, prompt engineering, and MLOps/LLMOps.
Strong understanding of ETL pipelines and system design.
Background in banking or insurance domain is preferred.
Strong stakeholder management and communication skills.

Key Responsibilities

Develop and deploy machine learning and NLP models for business use cases.
Work with large-scale data pipelines and distributed systems (e.g., PySpark, Spark).
Design and implement ETL pipelines and data transformation processes.
Collaborate with stakeholders to translate business needs into data-driven solutions.
Build and optimize solutions using Azure and Databricks platforms.
Apply LLMs, prompt engineering, and MLOps/LLMOps practices.
Ensure scalable, efficient, and production-ready data solutions.

Key Competencies

Data Science & Advanced Analytics
Cloud Data Engineering (Azure)
NLP & AI/ML Solutions
Distributed Systems (Spark)

Gazelle Global

Vacatures

Data Scientist