Decision Science- Sr. Analyst

Solytics Infotech; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Solytics Partners in India seeks a data science professional to tackle banking risk modelling challenges. You will develop and calibrate credit risk models, translate analytics into business guidance, and collaborate with Risk, Tech, and Governance teams.

Strong SQL and Python skills are required, with SAS helpful. The role focuses on Retail/Commercial Banking risk across model lifecycle and regulatory considerations.

Qualifications

• Degree in Mathematics, Statistics, Econometrics, Economics, Data Science, Computer Science, Engineering, or another quantitative discipline.
• Experience in Retail and/or Commercial Banking.
• Experience with model development, calibration, monitoring, validation, or governance.

Responsibilities

• Develop, calibrate, and monitor credit risk models and analytical solutions.
• Analyse large and complex datasets using SQL, Python and/or SAS.
• Apply statistical, predictive modelling, and advanced analytics techniques to business and risk problems.
• Assess model performance, assumptions, limitations, and risks.
• Support PD, LGD, EAD, IFRS 9, Basel and other credit risk modelling initiatives, where applicable.
• Conduct data quality checks, validation, and performance monitoring.
• Prepare model documentation and support model governance, audit, and regulatory approval activities.
• Translate analytical findings into clear business implications and recommendations.
• Work closely with Risk, Business, Technology, Data, and Governance stakeholders.

Skills

Statistical modelling

Data analysis

Regulatory knowledge

Education

Bachelor's degree in quantitative field

Tools

SQL

Python

SAS

Job description

Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting-edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions. Our offerings enable clients to streamline and future-proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether it's solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape.

Job Summary:

The role is focused on solving banking and credit risk problems using quantitative analysis, statistical modelling, and data science. The person will work on risk models across their lifecycle—from development and calibration to monitoring and governance- and translate analytical findings into actionable business and risk recommendations.

Key Responsibilities:

Develop, enhance, calibrate, and monitor credit risk models and analytical solutions.

Analyse large and complex datasets using SQL, Python and/or SAS.

Apply statistical, predictive modelling, and advanced analytics techniques to business and risk problems.

Assess model performance, assumptions, limitations, and risks.

Support PD, LGD, EAD, IFRS 9, Basel and other credit risk modelling initiatives, where applicable.

Conduct data quality checks, validation, and performance monitoring.

Prepare model documentation and support model governance, audit, and regulatory approval activities.

Translate analytical findings into clear business implications and recommendations.

Work closely with Risk, Business, Technology, Data, and Governance stakeholders.

Key Requirements:

Education

• Degree in Mathematics, Statistics, Econometrics, Economics, Data Science, Computer Science, Engineering, or another quantitative discipline.

Experience

• Experience in Retail and/or Commercial Banking.
• Experience with model development, calibration, monitoring, validation, or governance.

Technical Skills

• Strong SQL.
• Good to advanced Python.
• SAS is desirable.
• Strong statistical and analytical modelling skills.
• Experience handling large and complex datasets.
• Understanding of PD, LGD, EAD, IFRS 9, Basel and credit risk concepts.
• Understanding of consumer lending products and risk management.
• Regulatory knowledge such as PRA/FCA is desirable.