Job Description
## AI Business Analytics Engineer
**Department:** AI for Business Intelligence | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time | **CTC:** INR 16.0-38.8 LPA
### Role Overview
This position calls for an AI Business Analytics Engineer who can take ownership of core responsibilities within our AI for Business Intelligence team. The role is positioned at the mid level and reports into the broader AI for Business Intelligence charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai for business intelligence.
- Apply working knowledge of Data Preprocessing and TensorFlow/PyTorch to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 7 years of relevant experience (mid level).
- Working proficiency in: Data Preprocessing, TensorFlow/PyTorch, AI for Business Intelligence, Python, Cloud Platforms (AWS/GCP/Azure).
### Additional Notes
Internal job postings are open to employees who've completed a minimum tenure in their current role. The package is structured with a fixed component, performance bonus, and standard health coverage. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Relocation assistance may be extended for candidates moving from a different city, subject to approval. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Compensation includes standard statutory benefits along with performance-linked variable pay. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.
**Department:** AI for Business Intelligence | **Industry:** Artificial Intelligence (AI)
**Location:** Bhubaneswar | **Job Type:** Full-time | **CTC:** INR 16.0-38.8 LPA
### Role Overview
This position calls for an AI Business Analytics Engineer who can take ownership of core responsibilities within our AI for Business Intelligence team. The role is positioned at the mid level and reports into the broader AI for Business Intelligence charter.
### Key Responsibilities
- Own end-to-end delivery of tasks related to ai for business intelligence.
- Apply working knowledge of Data Preprocessing and TensorFlow/PyTorch to daily execution.
- Coordinate with cross-functional stakeholders within Artificial Intelligence (AI).
- Maintain documentation and reporting as required by the team lead.
- Flag risks and blockers early rather than at review checkpoints.
### Requirements
- M.Sc (Data Science) or equivalent qualification.
- 7 years of relevant experience (mid level).
- Working proficiency in: Data Preprocessing, TensorFlow/PyTorch, AI for Business Intelligence, Python, Cloud Platforms (AWS/GCP/Azure).
### Additional Notes
Internal job postings are open to employees who've completed a minimum tenure in their current role. The package is structured with a fixed component, performance bonus, and standard health coverage. There is a defined internal mobility path for people who want to specialise deeper or move into people management. Cross-functional exposure is built into the role by design, so the person will regularly interact with adjacent teams and leadership. Priorities can shift mid-week depending on business needs, so adaptability matters as much as technical depth. Relocation assistance may be extended for candidates moving from a different city, subject to approval. New joiners typically get a short structured onboarding before being handed independent ownership of their first deliverables. Compensation includes standard statutory benefits along with performance-linked variable pay. Performance is reviewed on a structured cycle, with clear criteria for movement into the next band. A typical day starts with reviewing priority tasks and syncing with the immediate team before moving into focused execution work. 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. The hiring process typically includes a screening round, a technical or functional assessment, and a final discussion with the reporting manager. Expect a mix of scheduled reviews, ad-hoc troubleshooting, and documentation as the workload shifts through the week. The environment rewards initiative - people who flag problems early and propose fixes tend to grow faster here. There's usually a block of uninterrupted time set aside for focused work, separate from meetings and coordination calls. No two days look identical - some are heavy on execution, others are spent largely in planning and cross-team discussions. Managers here tend to give context rather than instructions, leaving room for the individual to decide how a task gets done. Disagreement on approach is expected and welcomed, provided it's backed by reasoning rather than preference alone.