Nibruti Dash

• Partnered with engineering, compliance, and data teams to develop and deploy an AI-driven payroll compliance system using GPT-based prompt engineering. Engaged directly with clients across sectors to understand award interpretation challenges, validate payroll results, and ensure compliance with Fair Work entitlements. Led end-to-end analytical workflows from data ingestion and exploratory analysis to over/underpayment validation, delivering actionable insights and supporting accurate payroll remediation.
• Managed end-to-end implementation for 5+ clients, from data acquisition and validation to reporting, sign-off, and compliance remediation.
• Led the delivery team across multiple projects, maintaining close oversight of timelines, client communication, and results quality.
• Contributed to the development of an AI-powered payroll compliance system using GPT and prompt engineering for Fair Work Award rule extraction.
• Spearheaded the initial 6-month development phase translating industrial relations rules into structured, testable logic.
• Conducted EDA and diagnostic analysis to detect and validate overpayments and underpayments across various employment types.
• Delivered actionable insights and compliance reports, minimizing client risk and improving payroll accuracy.
• Facilitated weekly team stand-ups to track progress, address blockers, and align team goals; effectively managed resource planning and task allocation based on evolving priorities.
• Delivered tailored product demonstrations to prospective clients, showcasing technical capabilities and business value to support pre-sales and client onboarding efforts.
• As a Product Owner, led roadmap planning and implementation for internal tools and client-facing solutions; facilitated weekly team stand-ups, managed resource planning, and delivered tailored product demos to prospective clients to align business needs with product capabilities.

• Collaborated with cross-functional teams to identify and address technical challenges in the banking, insurance, and e-commerce industries. Conducted in-depth workshops and office hour sessions with clients to understand their unique problem statements and requirements. Recommended and implemented machine learning models to bridge gaps in client infrastructure and improve overall performance.
• Created and showcased demo projects to clients, effectively demonstrating the potential impact of proposed solutions.
• Evaluated different algorithms and techniques to meet client needs, delivering accurate predictions and time estimates based on historical data.
• Leveraged programming languages such as Python and SQL to develop high-quality code and machine learning pipelines, ensuring customer satisfaction and timely delivery.
• Recognised by SparkBeyond for successfully onboarding Grab, a major client.
• Appreciated by HDFC Bank for contributions in cloud migration, model building, and validation.
• Derived insights from unstructured data for Flying Tiger (a Danish variety store chain that has nearly 1,000 shops) which contributed to significant sales growth.
• Led successful POCs for clients like Aditya Birla Capital.
• Led the assisted onboarding process for more than 10 customers, ensuring seamless integration with the SparkBeyond Platform and driving customer success.

• Conducted regular data analysis to identify areas of non-compliance with security policies. Developed and implemented strategies to improve user compliance with security policies. Collaborated with cross-functional teams to identify and address security vulnerabilities.
• Led the design and implementation of a comprehensive database system, including both relational and non-relational databases.
• Developed and implemented predictive models to identify users who were unlikely to follow security policies and recommend targeted interventions.
• Led a team of 5 members in building the database, ensuring timely completion and high-quality deliverables.

• Collaborated with cross-functional teams to gather and manage client requirements for report development. Conducted feasibility analysis by assessing database schema, application workflow, and SSRS tool limitations to determine the viability of client requirements.
• Trained and mentored a team of 25 recruits on Jiva database schema and SSRS report development.
• Developed and deployed report coding using SQL Server Reporting Services (SSRS) to automate reporting processes.
• Streamlined report generation by creating complex SSRS reports and resolving production and UAT bugs.
• Contributed to significant time savings by developing reports that eliminated 180 hours of manual efforts per week for nurses.
• Received Spot Awards three times from ZeOmega Infotech Pvt. Ltd. for developing complex reports that improved efficiency and saved time.

Collaborated with clients to gather and analyse requirements for software development projects. Developed and maintained efficient and scalable software solutions using Microsoft tools and technologies. Conducted thorough testing and debugging to ensure the quality and functionality of software applications.

• Created and implemented SSRS reports using Microsoft tools, utilising tabular, graphical, and free formats to effectively present data.
• Upgraded and optimised the client's (MDWise) system from Jiva version 525 to 561, resulting in a 12% increase in performance speed. Also, introduced a new module for care management (maternity) and improved the user interface experience.
• Successfully managed client requirements for multiple clients simultaneously, delivering high-quality code within the estimated timeline.