We are looking for a Data Scientist with strong hands-on experience in
Machine Learning, Python, PySpark, and SQL to develop analytical models
within the wholesale banking domain. The candidate should possess a
problem-solving mindset and be experienced in the end-to-end model
development lifecycle.
Key Responsibilities:
Develop, validate, and deploy machine learning models for
banking-related use cases
Perform EDA and feature engineering to derive actionable insights from
data
Work on large-scale datasets using PySpark and SQL
Manage the complete model lifecycle, including model monitoring and
performance tracking
Collaborate with stakeholders to understand business problems and
translate them into analytical solutions
Clearly communicate model outputs and insights to both technical and
business stakeholders
Soft Skills:
Strong stakeholder management and communication skills
Ability to present findings and insights effectively
Expertise in Root Cause Analysis
Ability to clearly explain model outcomes to non-technical audiences
Experience working within an Agile framework
Prior exposure to the Banking domain
Good to Have:
Experience working on risk/fraud models in the banking domain
Certification in Data Science / Machine Learning
Education:
Bachelor’s degree in computer science, Software Engineering, MIS or
equivalent combination of education and experience
Key Skills:
Programming Languages:
Python (Pandas, NumPy), PySpark, SQL
Data Science Skills:
Exploratory Data Analysis (EDA)
Feature Engineering
Machine Learning (algorithms, performance metrics, model
evaluation)