About The Role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Consultant- Data Science and Analytics based in India.

This role offers the opportunity to apply advanced analytics and data science to real-world credit risk and business intelligence <challenges.You> will contribute to the development of predictive and analytical solutions serving financial services and consumer lending organizations.The position combines hands-on programming, statistical analysis, consulting, and client-facing problem <solving.You>’ll work with large-scale datasets and modern cloud and big-data technologies to uncover actionable insights.The role involves close collaboration with internal teams, external clients, and senior stakeholders across a global <environment.You>’ll have the opportunity to influence product innovation while helping customers make better risk and business decisions.This is a remote position based in India, with occasional travel and potential attendance at work-related events.

Accountabilities

Support the development of credit risk management, business intelligence, and advanced analytics solutions through consulting engagements and research.
Partner with cross-functional teams and clients to identify business opportunities and develop long-term, value-added analytical solutions.
Develop predictive risk management and business intelligence solutions for areas including credit cards, auto and mortgage lending, collections, and retail banking.
Conduct descriptive and prescriptive analyses across the consumer lending lifecycle, using techniques such as segmentation, scenario analysis, and sensitivity analysis.
Extract, manipulate, segment, and analyze large-scale datasets using tools and languages such as R, Python, SQL, Hive, and Spark across server- and cloud-based environments.
Translate complex analytical findings into clear, compelling insights and recommendations for clients, executives, and internal stakeholders.
Identify opportunities for customers to test, adopt, and expand the use of analytical products and services.
Manage multiple analytical assignments and projects simultaneously while maintaining quality, timelines, and stakeholder expectations.
Collaborate across a matrixed organization and contribute to a high-performance culture focused on innovation, excellence, and continuous improvement.

Requirements

Bachelor’s degree in statistics, applied mathematics, financial mathematics, engineering, operations research, or another highly quantitative discipline.
At least 6 years of professional analytical experience in financial services, consumer credit, or a related industry.
Strong analytical, critical-thinking, quantitative reasoning, and creative problem-solving capabilities.
Strong programming skills, with proficiency in a statistical language such as R; experience with SQL, Python, Hive, Pig, C/C++, Java, or similar technologies is advantageous.
Experience working with large datasets and modern big-data or cloud frameworks, ideally including Hadoop or Spark.
Strong understanding of data manipulation, statistical analysis, and analytical modeling techniques.
Excellent communication and presentation skills, with the ability to explain complex analytical concepts to technical, business, client, and executive audiences.
Strong project management skills and the ability to prioritize and deliver multiple assignments effectively.
Comfortable working independently with moderate supervision while collaborating effectively in a fast-paced, complex, and matrixed environment.
Advanced Excel capabilities, including formulas, macros, and pivot tables, are preferred.
Experience with Tableau or other data visualization platforms is preferred.
Familiarity with credit bureau data, consumer lending, and related business practices is a plus.
A Master’s or PhD in a quantitative discipline is preferred.
Experience working in a globally distributed organization is advantageous.
Strong English communication skills and willingness to travel approximately 10–20%.

Benefits

Remote work flexibility with occasional in-person attendance or travel as required.
Flexible time-off policies designed to support work-life balance.
Opportunities for continued professional development, including support for tuition reimbursement, conferences, and seminars.
Access to modern computing environments, cloud technologies, big-data platforms, and advanced analytics tools.
Opportunities to explore new data sources, statistical methodologies, machine learning approaches, and emerging technologies.
Collaborative environment with opportunities to work alongside experienced analytics and data professionals.
Career development opportunities focused on strengthening existing skills and building new capabilities.
Comprehensive employee programs and resources supporting professional, physical, mental, and personal well-being.