StrideOne - Senior Risk Analyst (1-4 yrs)

Company Profile:

StrideOne is more than an NBFC; we are a financial institution for Indian startups and businesses, offering a full suite of financial services under the 'One' umbrella. As a new age finance partner, our "Entrepreneur-first approach and Agile framework" enable us to provide full-stack solutions tailored to the unique needs of unicorns, SME's and MSMEs across various industries.

With our in-house technology and experienced finance team, StrideOne delivers bespoke financial programs that cater to the specific requirements of each sector. Our journey as a group is just beginning, yet we already boast of 100+ startups, echoing Stride Ventures legacy and commitment to empowering entrepreneurs.

At StrideOne, we believe that an organisation is built by its people. We foster a very open and welcoming culture that encourages honest conversations, analytical thinking, and innovation, free from bias and hierarchical constraints.

Role Overview:

The Senior Risk Analyst will play a critical role in leveraging data analytics and statistical modeling to assess, identify, and mitigate risks. This role is pivotal in developing and implementing risk models and early warning signals to safeguard portfolio health and enhance decision-making.

Key Responsibilities:

1. Conduct comprehensive risk assessments and implement mitigation strategies.

2. Develop and deploy risk models tailored to organizational needs.

3. Implement and monitor Early Warning Signals (EWS) for proactive risk management.

4. Own and manage model validation, portfolio risk metrics, and EWS performance metrics.

Key Skills & Competencies:

- Proficiency in SQL, Python/R for data analysis and model development.

- Expertise in statistical modeling and data manipulation.

- In-depth knowledge of credit risk concepts and frameworks.

- Candidates from similar roles in organizations specializing in risk management, financial services, or analytics-driven functions.

Profile Requirements:

Education:

- Minimum: Graduation or Master's degree.

- Preferred: Graduation/Master's with Statistics as one of the subjects.

Experience:

- Required: Hands-on experience in data analysis and risk modeling.

- Preferred: Exposure to dimensionality reduction, regularization techniques, and feature selection.