. The role involves developing predictive and statistical models to optimize marketing, risk, and customer lifecycle strategies. The ideal candidate will combine technical expertise in data science with deep business understanding to generate insights that improve acquisition, cross-sell, retention, and portfolio health across retail and commercial banking segments.
Key Responsibilities:
Develop and deploy predictive models
for use cases such as credit risk, customer segmentation, attrition prediction, and marketing campaign optimization.
Apply advanced machine learning and statistical techniques
to derive actionable insights from large, structured, and unstructured banking datasets.
Collaborate closely with business stakeholders
(e.g., marketing, credit risk, collections, customer experience teams) to define analytical problems and deliver measurable business impact.
Perform exploratory data analysis and feature engineering
to identify key drivers of business outcomes.
Leverage tools such as Python, R, and SQL
for model development, validation, and automation.
Create data visualizations and dashboards
(Tableau, Power BI, etc.) to communicate insights effectively to senior business and technical leaders.
Monitor and maintain model performance
post-deployment, ensuring models stay compliant and relevant to changing market dynamics.
Ensure regulatory compliance and data governance
across all modelling activities in alignment with banking policies.
Stay current with emerging modeling methodologies
and innovations in AI/ML relevant to financial analytics.
Qualifications & Requirements:
6+ years of experience
in statistical modelling, predictive analytics, or machine learning within the
banking or financial services domain
.
Strong understanding of
banking data structures
-- including customer, transaction, credit, and product data.
Proficiency in Python, R, SQL
and familiarity with modelling libraries (e.g., Scikit-learn, XGBoost, TensorFlow).
Strong grasp of
statistical concepts
(e.g., regression, classification, time-series forecasting, hypothesis testing).
Proven ability to
translate analytical findings into business recommendations
with clear ROI impact.
Experience with
data visualization tools
such as Tableau or Power BI (good to have)
Bachelor's or Master's degree in
Statistics, Mathematics, Data Science, Computer Science, Economics, or related field.
Preferred Skills (Good to Have):
Experience in
credit risk modelling
,
marketing mix modelling
, or
customer lifetime value analysis
.
Exposure to
cloud-based analytics platforms
(AWS, Azure or GCP).
Familiarity with
model risk governance frameworks
and regulatory expectations (e.g., SR 11-7, CCAR, Basel).
About eClerx
eClerx is a global leader in productized services, bringing together people, technology and domain expertise to amplify business results. Our mission is to set the benchmark for client service and success in our industry. Our vision is to be the innovation partner of choice for technology, data analytics and process management services. Since our inception in 2000, we've partnered with top companies across various industries, including financial services, telecommunications, retail, and high-tech. Our innovative solutions and domain expertise help businesses optimize operations, improve efficiency, and drive growth. With over 18,000 employees worldwide, eClerx is dedicated to delivering excellence through smart automation and data-driven insights. At eClerx, we believe in nurturing talent and providing hands-on experience.
About eClerx Digital
eClerx Digital is the trusted partner of choice to many of the world's largest global brands for creative production, e-commerce/web operations, and analytics and insights services. We help clients maximize the results of their digital activities across the customer journey. Global industry leaders partner with us to cost-effectively scale their digital activities by leveraging our highly skilled blended resource model.
To know more about us, visit https://eclerx.com
eClerx is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, or any other legally protected basis, per applicable law.
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