Aug 2024 – Oct 2025 · 1 yr 2 mos · Bloomington, Indiana, United States · Hybrid

• Project: The Multiscale Human: Exploring Human Body in 3D Across Scales in Virtual Reality
• Translated complex data processing needs into optimized SQL queries and Python scripts, creating relevant, data-driven reports for various cross-functional teams in medical research and and supported the development team in transforming this data into 3D visual models for research and VR applications.
• Utilized Tableau and Power BI to design interactive visualizations, making anatomical data accessible to non-technical stakeholders, resulting in faster decision-making for 3D human body exploration in VR.
• Conducted statistical analysis on multi-scale human body data, leveraging pandas, SciPy, and Scikit-learn to identify key trends and ensure accurate representations in virtual environments.
• Developed timely, accurate, and scalable reporting solutions for internal and external stakeholders, significantly reducing turnaround time for data processing and model validation.
• Worked extensively with medical and scientific datasets, optimizing data pipelines and integrating anatomical metrics to improve model precision and usability in VR applications.
• Collaborated with cross-functional teams, including biomedical engineers, data scientists, and VR developers, to deliver projects on time and within budget, consistently achieving key milestones.
• Created and maintained documentation and training materials, ensuring the team operated efficiently and remained aligned with project goals related to data processing and analysis.
• Conducted root cause analysis to enhance data quality and processing efficiency, continuously improving data workflows for high-resolution anatomical modeling.
• Participated in critical meetings with stakeholders, providing insights and technical expertise on data analysis, visualization, and statistical modeling to guide project strategy and execution.

May 2024 – Dec 2024 · 7 mos · Bloomington, Indiana, United States · Hybrid

• Developed an LDA model using Python (SpaCy, Gensim) to analyze pipeline documents, identify stakeholders, and applied advanced NLP techniques like VADER for sentiment analysis and topic modeling of multi-source feedback, highlighting strategic and environmental impacts.
• Worked on the development of a predictive analytics model, leveraging data processed through ETL tools, to reduce infrastructure project costs through data-driven forecasting and risk assessment.
• Fostered collaboration between technical teams and business stakeholders, aligning the project with strategic business goals and enhancing stakeholder engagement, leading to a 70% increase in project alignment.
• Worked on cost-reduction strategies by analyzing data patterns, minimizing environmental impacts, and supporting effective decision-making in energy development.
• Conducted qualitative data analysis and sentiment analysis using MAXQDA to identify key themes and patterns in project documents, improving the understanding of stakeholder feedback and created dashboards using Power BI based on the feedback, aiding in the refinement of project strategies.
• Designed and implemented data pipelines using Python and ETL tools (Talend, Alteryx) to automate data extraction, transformation, and loading processes, reducing data processing time by 45% and increasing data interpretation speed by 25%.

Mar 2019 – Jul 2021 · 2 yrs 4 mos · Bengaluru Area, India · On-site

• Managed several key client accounts, including DXC, serving as the primary point of contact to understand client needs, deliver tailored recruitment strategies, and drive an 80% increase in client satisfaction.
• Led large-scale recruitment initiatives across IT and non-IT sectors, successfully closing over 1000+ positions while improving talent retention through optimized hiring pipelines.
• Analyzed business operations data and recruitment performance, developing automated dashboards using Tableau and Power BI for real-time workforce planning, operational efficiency, and executive reporting.
• Performed data-driven workforce analytics by leveraging SQL and Python (pandas, NumPy) to identify hiring trends, optimize talent acquisition strategies, and reduce recruitment cycle times.
• Designed and implemented KPI tracking systems using Excel, SQL, and BI tools to monitor business process efficiency, forecast revenue, and support strategic planning based on market research.
• Developed cost-effective recruitment solutions using business process reengineering and data analytics, reducing hiring costs by 60% and operational expenses by 130%.
• Conducted cost-benefit analyses and financial modeling to assess recruitment expenditures, enabling strategic cost-cutting measures and recruitment process improvements.
• Collaborated with cross-functional teams to streamline data workflows by integrating CRM systems and Workday into recruitment analytics, enhancing reporting consistency and efficiency.
• Trained and mentored a team of entry-level HR staff, standardizing global client management processes and aligning service delivery with client business goals.
• Documented and maintained analytics methodologies, ensuring reproducibility, transparency, and best practices in business intelligence reporting.

Nov 2017 – Feb 2019 · 1 yr 3 mos · Bangalore Urban, Karnataka, India · On-site

• Vortex Crew Technologies, Bangalore
• Managing Director, November 2017 – January 2019
• Proposed and launched new business lines. My responsibilities also included prospecting for new clients, giving presentations, negotiating contracts, securing required legal approvals. Managed onsite and remote staff, enhanced employee relations, and decreased operating expenses. I have also cultivated strong business relationships and resolved escalated issues in an efficient, timely manner.
• Spearheaded the hiring, training, and mentoring of a multi-unit management team. Coached and mentored employees to effectively execute the operations and drive customer service and revenue. I have developed improved policies and procedures to maximize productivity while controlling labor costs according to the client requirement.

May 2017 – Oct 2017 · 5 mos · Hyderabad, Telangana, India · On-site

• Managed customer data for account recovery processes, ensuring data privacy and security in line with business requirements to enhance customer trust and satisfaction.
• Resolved critical customer issues related to Gmail account recovery, improving user privacy and enhancing the overall user experience based on UX Research, by implementing efficient and secure data management practices.
• Established data governance practices, including data quality checks, data cataloging, and access control measures to maintain data integrity and security across data warehousing systems.
• Collaborated with clients and internal teams to understand business needs, tailoring solutions to optimize account recovery processes, which contributed to a 70% increase in operational efficiency.
• Developed and optimized SQL-based data processing scripts for data validation and cleansing, ensuring data quality and consistency while complying with privacy regulations.
• Supported and trained new team members on customer interaction strategies and user-centric design, contributing to improved business operations and enhanced client support services.