Job Title:
Lead Data Scientist – Wholesale Banking
Location:
Bangalore
Employment Type:
Full-Time
Experience Required:
8+ Years
About the Role:
We are seeking a highly skilled and experienced
Lead Data Scientist
with a strong background in banking, specifically in
wholesale banking
. The ideal candidate will have deep expertise in data science, machine learning, and AI-driven solutions, coupled with leadership experience to drive data-centric initiatives. You will work closely with stakeholders, product owners, and technical teams to shape data strategies, lead AI projects, and deliver impactful insights that align with business objectives.
Key Responsibilities:
Lead end-to-end data science projects focused on
wholesale banking
domains, including risk management, customer segmentation, credit scoring, and fraud detection.
Develop and deploy machine learning models and AI-driven solutions to solve complex business challenges.
Collaborate with
product owners
,
AI project managers
, and cross-functional teams to align data strategies with business goals.
Apply advanced analytics techniques to enhance customer insights, improve operational efficiency, and optimize financial outcomes.
Manage and mentor a team of data scientists and machine learning engineers, fostering a culture of innovation and continuous learning.
Ensure adherence to data governance, privacy regulations, and industry best practices.
Translate business requirements into data-driven solutions and present actionable insights to senior stakeholders.
Required Skills & Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
8+ years of experience in
data science
and
machine learning
, with at least 3 years in a leadership role.
Strong domain knowledge in
wholesale banking
, including regulatory compliance, risk analysis, and customer profiling.
Proficiency in Python, R, SQL, and relevant data science libraries (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch).
Hands-on experience with cloud platforms such as
AWS
,
Azure
, or
GCP
.
Expertise in AI/ML techniques such as supervised and unsupervised learning, natural language processing (NLP), and generative AI.
Familiarity with
MLOps
frameworks and deployment pipelines.
Strong communication skills with the ability to present complex data insights to both technical and non-technical stakeholders.
Preferred Qualifications:
Experience working in
wholesale banking
or financial services.
Knowledge of
risk modeling
,
credit analytics
, and
fraud detection
in banking environments.
Exposure to AI governance, ethical AI practices, and regulatory standards.
Experience leading cross-functional teams and managing AI-driven product lifecycles.
