 Developed employee termination risk scores by putting into practice a flight risk prediction model. proactively identified flight risks by utilizing sophisticated predictive analytics and machine learning algorithms. This allowed for prompt interventions and deliberate retention efforts, which improved workforce stability.  Intelligent Succession Recommendation model: recommend the successors to all jobs in Honeywell based on past job movement history, skills, performance and years of experiences. Implemented advanced algorithms to optimize stock levels, reducing both stockouts and overstock situations. Fostered cross-functional collaboration to integrate diverse data sources, ensuring a comprehensive and accurate forecasting model. Utilized natural language processing techniques to automate the categorization of survey comments, streamlining the analysis process. Developed a scalable framework for continuous improvement based on feedback categorization insights, enhancing decision-making capabilities. Established standardized protocols for project initiation, execution, and evaluation to ensure consistency and quality across data science initiatives. Collaborating with key stakeholders to understand business needs and translate them into data science solutions. Effectively communicating insights and recommendations to non-technical stakeholders. Driving measurable business outcomes through data-driven insights and solutions. Employing a combination of SQL, Excel, and R Language to conduct thorough data analysis, identifying patterns and trends critical for informed decision-making.

 Transforming current Honeywell’s Human Resource Data Analytics Database on Honeywell Forge platform Developing prediction model for generating flight risk score (employee termination risk)  Providing recommendation to manager/HR based on FRS score  Analyzing raw data, data cleansing transformation using (SQL, excel & R Language), drawing conclusions providing recommendations  Creating and executing statistical strategies to exceed the prescribed goals  Developing R & Python program complying with the coding standards defined by technical management  Designing application to compute commute distance using google map APIs.  Assisting with encoding, testing, debugging, re-verification of provided solution, visualizations and documenting case studies for final delivery.

 Generated Aerospace Navigational Database every 28 days with multiple DB/FMS requirement  Developed detailed project schedules through effective planning and forecasting  Evaluated team performance and provided constructive feedback for areas of improvement  Managed a team of consultants and spearheaded their on-shift duties

 Conducted project meetings successfully by coordinating with all users, technical staff and support personnel  Supported onsite location multiple times  Played a key role in critical and immediate client deliveries  Performed ROM for the new requests  Performed initial analysis and updating risk analysis sheets  Updated PL/SQL codes as per the requirement for fitting the new features for the new/existing FMSs  Resolved production queries

 Steered efforts in coding, testing and fixing programming errors  Created and executed unit/regression test cases  Conducted various quality assurance tests to discover errors and optimize usability  Attended weekly client meetings to discuss the specifics of the automated tests

 Steered efforts in coding, testing and fixing programming errors  Created and executed unit/regression test cases  Conducted various quality assurance tests to discover errors and optimize usability  Attended weekly client meetings to discuss the specifics of the automated tests

Internship during last semester of my Master's degree