Job Description
An opening exists for a Senior AI Consultant – Business Intelligence to join the Artificial Intelligence (AI) vertical, focused on AI for Business Intelligence. This is a senior level opening based out of Nagpur, offered on a hybrid basis.
The ideal candidate holds M.Sc (Data Science) and brings roughly 11 years of hands-on exposure to ai for business intelligence. Day-to-day, the work draws heavily on Data Preprocessing, Cloud Platforms (AWS/GCP/Azure), Python, Natural Language Processing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 35.1-86.3 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Learning and certification support is available for tools and frameworks directly relevant to the role.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Compensation includes standard statutory benefits along with performance-linked variable pay.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The next logical step from this position is a senior or lead-track role within the same function.
Interested candidates should be prepared to walk through relevant past work during the interview process. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving.
References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
This role offers a genuine opportunity to build depth in AI for Business Intelligence while working alongside an experienced team.
The ideal candidate holds M.Sc (Data Science) and brings roughly 11 years of hands-on exposure to ai for business intelligence. Day-to-day, the work draws heavily on Data Preprocessing, Cloud Platforms (AWS/GCP/Azure), Python, Natural Language Processing, and the person will be expected to apply these skills independently rather than under constant supervision.
Compensation for this position is structured around INR 35.1-86.3 LPA, in line with market standards for senior level roles within artificial intelligence (ai).
New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Learning and certification support is available for tools and frameworks directly relevant to the role.
Leave policy follows standard industry norms, including earned leave, sick leave, and public holidays as applicable. Compensation includes standard statutory benefits along with performance-linked variable pay.
Relocation assistance may be extended for candidates moving from a different city, subject to approval. Skip-level conversations with senior leadership are encouraged at least twice a year to discuss career direction.
The package is structured with a fixed component, performance bonus, and standard health coverage. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions.
Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. The next logical step from this position is a senior or lead-track role within the same function.
Interested candidates should be prepared to walk through relevant past work during the interview process. Mornings are usually spent on planning and status reviews, while the rest of the day is given over to hands-on delivery and problem-solving.
References may be requested closer to the offer stage rather than at the start of the process. Internal job postings are open to employees who've completed a minimum tenure in their current role.
High performers in this role typically move into a broader ownership scope within 18-24 months. The organisation has historically promoted from within for a majority of its senior and lead openings.
In addition to fixed pay, the role carries eligibility for annual appraisals and merit-based increments. The role alternates between independent deep work and short coordination huddles with stakeholders across functions.
Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. 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.
There is a defined internal mobility path for people who want to specialise deeper or move into people management. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls.
Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Most days include at least one review checkpoint where progress is discussed against the plan for the week. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done.
Applications without a clear summary of relevant experience are less likely to be shortlisted for the first round. Work culture here leans collaborative, with regular knowledge-sharing sessions and an open-door policy for raising concerns.
The team follows a flat structure where ideas are evaluated on merit rather than hierarchy, and feedback flows in both directions. Candidates are encouraged to highlight measurable outcomes from previous roles rather than just responsibilities held.
The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Shortlisted applicants will be evaluated on both domain knowledge and practical problem-solving ability.
This role offers a genuine opportunity to build depth in AI for Business Intelligence while working alongside an experienced team.