Job Description
We are looking to onboard an AI Predictive Risk Lead to strengthen our AI-driven Risk Management function within Artificial Intelligence (AI). This is a senior level opening based out of Hyderabad, offered on a full-time basis.
The ideal candidate holds M.Sc (Data Science) and brings roughly 16 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Machine Learning, Neural Network Architectures, Natural Language Processing, Python, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 20.5-71.8 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The package is structured with a fixed component, performance bonus, and standard health coverage.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
High performers in this role typically move into a broader ownership scope within 18-24 months. The next logical step from this position is a senior or lead-track role within the same function.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation has historically promoted from within for a majority of its senior and lead openings. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.
The ideal candidate holds M.Sc (Data Science) and brings roughly 16 years of hands-on exposure to ai-driven risk management. Day-to-day, the work draws heavily on Machine Learning, Neural Network Architectures, Natural Language Processing, Python, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 20.5-71.8 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
Most days include at least one review checkpoint where progress is discussed against the plan for the week. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Benefits include health insurance, provident fund contributions, and paid leave in line with company policy.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Internal job postings are open to employees who've completed a minimum tenure in their current role.
The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. The package is structured with a fixed component, performance bonus, and standard health coverage.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
High performers in this role typically move into a broader ownership scope within 18-24 months. The next logical step from this position is a senior or lead-track role within the same function.
Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns. The organisation places a premium on ownership; once a task is assigned, the expectation is to see it through without hand-holding. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week.
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments.
No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The organisation has historically promoted from within for a majority of its senior and lead openings. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
We value consistency and follow-through more than flashy credentials - if that matches how you work, apply in.