Srujan *********
Generative AI Developer
Experienced Generative AI Developer with over 5 years of expertise, leveraging a strong programming foundation in Python, SQL, and Power BI. Demonstrated ability to creatively tackle complex problems and effectively communicate technical concepts to diverse stakeholders. Driven by a deep interest in uncovering insights from data and driving data-driven decision-making processes. Recognised for translating data findings into clear and actionable reports using data science and AI techniques, empowering informed decision-making at all organizational levels.
Skills
AWS, Beautiful-Soup, Computer Vision, Data Transformation, DAX, Decision Trees, GIT, Linear Regressions, Logistic Regressions, Microsoft Power BI, NumPy, OpenCV, Pandas, Power Query, Python, SnowFlake, SQL.
Education
2023
Masters of Artificial Intelligence at Royal Melbourne Institute of Technology
2017
Bachelor's of Engineering at M.S.Ramaiah Institute of Technology
Experience
July 2023 - Nov 2023: Data Science Research Project Assistant (Intern) at Robotic Assisted Surgical Performance Assessment
– Led the development of a video-based performance assessment system to objectively evaluate surgeons' skills in robotic-assisted suturing, dissection, and tissue manipulation, thereby reducing manual effort for skill evaluation.
– Recognised for automating surgical skill assessment, streamlining processes, facilitating multidisciplinary collaboration, and providing subject matter expertise to ensure the effectiveness of the assessment system and successful project execution.
– Optimised the deep learning model with a client-provided dataset of robot-assisted surgery recordings, achieving a 70% accuracy rate in identifying instrument handling proficiency within surgical videos.
– Utilised OpenCV for video pre-processing tasks such as frame extraction, optical flow analysis, and stabilisation to significantly improve data quality and reduce processing time by 40%, streamlining the assessment process.
July 2021 - July 2022: Data Analyst at Infosys
– Leveraged advanced data exploration techniques within ServiceNow ITSM & CSM modules to drive a 20% improvement in operational efficiency.
– Developed seamless integrations between ServiceNow, Salesforce, Datadog, & Jira, streamlining data consolidation and simplifying reporting processes.
– Crafted user-friendly data dashboards & reports with actionable insights, empowering stakeholders to make informed, data-driven decisions.
– Analysed ITSM (incident, problem, change request data), CSM, HR, and CMDB data using advanced exploration techniques to identify trends, optimize processes, and support data-driven decisions.
– Analysed, documented, and reported user survey results, leading to an 18% improvement in customer communication processes driven by data insights.
Jan 2019 - Apr 2021: Data Analyst at Accenture
– Streamlined ServiceNow data import, transformation, and reporting processes, resulting in a 20% improvement in data accuracy and platform efficiency.
– Developed data visualizations within ServiceNow dashboards to empower stakeholders with real-time KPI insights for data-driven decision-making.
– Partnered with business analysts to translate business needs into actionable reporting structures, ensuring reports aligned with strategic objectives.
– Utilised expertise in data analysis, troubleshooting, and scripting (JavaScript) to identify and resolve data quality challenges, ensuring clean data ready for analysis.
– Mentored junior developers, providing training and support to enhance their data analysis skills within the ServiceNow platform.
Oct 2017 - Jan 2019: Test Analyst at Accenture
– Leveraged SQL expertise to design and execute targeted data quality checks, identifying and rectifying issues such as missing values, duplicates, and inconsistencies. This ensured compliance with external network mandates (Visa, MasterCard, etc.) within the STAR Station application for debit processing.
– Developed automated testing processes using SQL stored procedures. This reduced manual effort, ensured consistent test execution, and led to a 20% efficiency improvement in testing critical financial transactions.
– Implemented a comprehensive testing strategy (functional, regression, sanity, integration, user acceptance) for the STAR Station application. This proactive approach identified and mitigated transaction defects, preventing potential financial losses for First Data.
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