Pallavi Magar

Technical Skills:

• Data Analysis & Visualization:
• Proficiency in Microsoft Excel (including advanced features like Power Pivot).
• Data manipulation and visualization using Python.
• Query writing and data extraction using SQL.
  
• Process Improvement:
• Documenting workflows for data warehouse integration.
• Identifying inefficiencies and implementing strategies to boost utilization rates.
  
• Data Reporting:
• Creating actionable insights from survey data.
• Developing visual reports to communicate findings effectively.
  
• Technology Implementation:
• Designing and implementing a QR code-based system for resource access.
  

Soft Skills:

• Problem-Solving: Developing innovative solutions, such as the QR code system, to improve resource accessibility.
  
• Collaboration: Coordinating with stakeholders to ensure seamless process flows and data integration.
• Analytical Thinking: Interpreting survey results to identify patterns and implement data-driven strategies.
• Communication: Effectively presenting survey findings and recommendations through visual reports.
  

Impactful Outcomes:

• Enhanced data-driven decision-making by turning survey insights into actionable strategies.
• Improved user experience with increased resource interaction and satisfaction levels.
• Boosted resource efficiency and accessibility by integrating innovative tools like QR codes.

Technical Skills:

• Statistical Analysis:
• Conducting statistical analysis and deriving actionable conclusions to solve real-world problems.
• Expertise in SQL for data extraction, manipulation, and analysis.
  
• Problem Identification and Resolution:
• Identifying key productivity issues affecting administrative teams.
• Designing strategies based on data insights to address productivity loss.
  
• User Interface (UI) Development:
• Developing and testing UI prototypes with a focus on usability and user experience.
• Applying software engineering principles to improve design and functionality.
• Cross-Functional Collaboration:
• Working with diverse teams to share insights and inform report development.
• Translating technical findings into actionable recommendations for various stakeholders.
  

Soft Skills:

• Analytical Thinking: Analyzing data to identify root causes of productivity loss and proposing targeted solutions.
• Innovation: Enhancing onboarding processes through improved UI prototypes, reducing onboarding time.
• Team Collaboration: Engaging with cross-functional teams to ensure solutions align with organizational goals.
• Communication: Clearly presenting findings and recommendations to improve processes and productivity.
  

Impactful Outcomes:

• Directly addressed productivity loss by pinpointing and resolving the top three causes.
• Improved user experience through enhanced UI prototypes, resulting in a 15% reduction in onboarding time.
• Facilitated data-driven decision-making that improved customer service and streamlined administrative operations.

Technical Skills:

• Data Analysis and Visualization:
• Proficiency in Excel (including Power Pivot) for data analysis and reporting.
• Creating business intelligence dashboards to track and analyze key metrics.
  
• Predictive Analytics:
• Designing and testing machine learning models for forecasting equipment failures.
• Applying predictive analytics to improve operational efficiency.
• Programming and Tools:
• Working with Snowflake for advanced data processing and analysis.
• Developing algorithms and models leveraging machine learning and AI techniques.
• Data Pipeline Optimization: Enhancing data flow processes to reduce costs and streamline operations.
  
• System Integration: Leveraging Electronic Medical Record (EMR) systems to inform sales and compensation strategies.
  
• Feature Engineering: Developing a feature recommendation system to drive customer satisfaction and account expansion.

Soft Skills:

• Strategic Decision-Making: Informing key business strategies based on sales performance and compensation analysis.
• Problem-Solving: Addressing operational challenges, such as unexpected downtime and equipment returns, through data-driven approaches.
• Innovation: Developing cutting-edge solutions, like predictive models and recommendation systems, to achieve measurable results.
• Collaboration: Working across teams to implement dashboards and analytics solutions that align with organizational goals.
• Customer Focus: Enhancing customer satisfaction through personalized feature recommendations.

Impactful Outcomes:

• Enhanced revenue for medicine service lines through data-driven decision-making.
• Minimized unexpected downtime by implementing predictive models for equipment failure.
• Reduced return-related costs through optimized data pipeline processes.
• Boosted customer satisfaction and achieved account expansion with a feature recommendation system.

Technical Skills:

• Predictive Modeling: Developed and deployed machine learning algorithms for scenario planning and predictive analytics.
• Programming: Proficiency in Python and Java frameworks for machine learning model development.
• Data-Driven Decision-Making: Implemented models that enhanced decision-making processes across departments.
• Operational Analysis: Applied advanced mathematics and computer science principles to improve workflows and refine business strategies.
• Model Engineering: Engineered predictive models to optimize processes and improve accuracy.

Soft Skills:

• Strategic Thinking: Enhanced operational workflows through thoughtful model development and scenario planning.
• Problem-Solving: Streamlined processes and tackled complex challenges with innovative machine learning solutions.
• Collaboration: Worked across departments to align model outputs with organizational goals.
• Attention to Detail: Ensured accuracy and reliability in predictive analytics tasks.

Impactful Outcomes:

• Enhanced operational workflows, leading to refined business strategies.
• Improved decision-making processes across departments with tailored machine learning models.
• Achieved greater accuracy in predictive analytics tasks, streamlining departmental workflows.

Technical Skills:

• Data Analysis and Modeling:
• Expertise in market analysis and customer segmentation for strategic decision-making.
• Development of statistical models to improve marketing strategies and operational efficiency.
• Data Management:
• Proficiency in data extraction from EDW (Enterprise Data Warehouse) systems.
• Standardizing data analysis practices across departments.
• People Analytics: Implementation of tools for analyzing workforce data to inform strategic decisions.
• Process Optimization: Streamlining reporting and operational processes for efficiency improvements.

Soft Skills:

• Cross-Functional Collaboration: Partnered with diverse teams to align data processes with organizational goals.
• Strategic Thinking: Applied quantitative insights to drive targeted initiatives across marketing, sales, and supply chain management.
• Problem-Solving: Innovated solutions to reduce costs and enhance reporting and operational efficiencies.

Impactful Outcomes:

• Improved marketing, sales, and supply chain strategies through customer segmentation and market analysis.
• Enhanced cost efficiency with statistical modeling for strategic marketing and process improvements.
• Streamlined reporting processes, increasing efficiency and enabling quicker decision-making.
• Established a standardized approach to people analytics, improving communication and alignment across teams.

Technical Skills:

• Risk Analysis and Mitigation: Conducted data-driven risk assessments to enhance project success rates.
• Process Improvement:
• Utilized Python to restructure operational solutions and increase efficiency.
• Implemented continuous improvement strategies using data analysis and reporting tools.
• Data Engineering:
• Automated ETL (Extraction, Transformation, Loading) processes for diverse datasets using Python
• Ensured accuracy and speed in analytical reporting through automation.
• Data Security: Designed and executed data security scripts to safeguard data during processing.
• Operational Reporting: Developed advanced reporting mechanisms to streamline decision-making and operational oversight.

Soft Skills:

• Analytical Thinking: Applied critical thinking to identify operational inefficiencies and mitigate risks.
• Problem-Solving: Designed innovative solutions to automate and optimize processes.
• Efficiency Focus: Prioritized accuracy and speed in data processing and reporting.
• Collaboration: Supported cross-functional initiatives with secure and efficient data solutions.

Impactful Outcomes:

• Increased on-time project completions through effective risk management.
• Enhanced operational efficiency with restructured solutions and continuous improvements.
• Improved reporting speed and accuracy by automating data processing workflows.
• Strengthened data security and integrity during analytical reporting initiatives.

Master’s in Data Science and Business Analytics

Wayne State University Aug 2023- Dec 2024

• Data Analysis & Visualization: Proficiency in tools like Python, R, SQL, and Tableau for analyzing large datasets and presenting actionable insights.
  Hands-on experience with Power BI for creating dashboards to communicate key metrics effectively.
• Machine Learning & Predictive Analytics: Designed and implemented machine learning models for classification, regression, clustering, and time series forecasting.
  Worked on projects involving natural language processing (NLP) and deep learning, applying techniques like sentiment analysis and predictive modeling.
• Big Data and Cloud Platforms: Knowledge of handling large-scale datasets using tools like Hadoop, Spark, and AWS.
  Experience with data warehousing and ETL processes to manage and analyze structured and unstructured data.
• Statistical and Mathematical Foundations: In-depth understanding of statistical modeling, probability, and optimization techniques.
  Application of multi-variate analysis, A/B testing, and decision trees for data-driven decision-making.

What I Can Bring to the Table:

• Data-Driven Decision-Making:Proficiency in extracting, analyzing, and interpreting data to support strategic decisions and solve business challenges.
• Scalable Solutions:Ability to build predictive models and analytics solutions that scale effectively to meet organizational needs.
• Innovation in Analytics:Experience in developing innovative analytics tools, dashboards, and systems that enhance operational efficiency and customer satisfaction.
• Cross-Domain Expertise:Practical experience in applying data science to domains such as healthcare analytics, supply chain optimization, and customer segmentation.
• Continuous Improvement:Strong focus on identifying trends, optimizing processes, and providing actionable insights to support business growth.
• Clear Communication with Non-Technical Stakeholders:Skilled at translating complex data analytics findings into clear, actionable insights tailored to non-technical stakeholders, fostering better understanding and alignment across teams.