Data Analyst Machine Learning
Resume:
Vandana Reddy
DATA ANALYST
EDUCATION
SUMMARY
TX, USA
****************@*****.***
Master of Science in Computer
Science - University of North Texas,
Denton, Texas
Bachelor of Technology in Electronics
& Communication Engineering - Sri
Venkateswara College of Engineering,
India
SKILLS
Methodologies: SDLC, Agile, Waterfall
Languages: Python, SQL, R
Packages: NumPy, Pandas, Matplotlib,
SciPy, Scikit-learn, TensorFlow, Seaborn
Visualization Tools: Tableau, Power BI,
Advanced Excel (Pivot Tables,
VLOOKUP)
IDEs: Visual Studio Code, PyCharm,
Jupyter Notebook
Database Management: MySQL,
PostgreSQL, MongoDB, SQL Server,
Oracle
Cloud Platform: AWS, MS Azure
Other Technical Skills: SSIS, SSRS,
Machine Learning Algorithms,
Probability distributions, Confidence
Intervals, ANOVA, Hypothesis Testing,
Regression Analysis, Linear Algebra,
Advance Analytics, Data Mining, Data
Visualization, Data warehousing, Data
transformation, Data Storytelling,
Association rules, Clustering,
Classification, Regression, A/B Testing,
Forecasting & Modelling, Data
Cleaning, Data Wrangling, Jira
Soft Skills: Time management,
Leadership, Management, Problem-
solving, Negotiation, Decision-Making,
Documentation and Presentation,
Verbal communication.
Operating System: Windows, Linux,
Mac OS
Data Analyst with 4+ years of proven expertise in gathering, analyzing, and visualizing data to drive strategic decision-making and optimize business processes. Proficient in SQL, Python, Power BI and Tableau, adept at creating impactful reports and dynamic dashboards. Skilled in ETL processes, data transformation, and database management. Demonstrated ability to collaborate with cross-functional teams, improve data analysis methodologies, and deliver actionable insights. Strong problem-solving and communication skills, with a track record of enhancing efficiency and reducing costs. PROFESSIONAL EXPERIENCE
Data Analyst United Healthcare, TX Oct 2022 – Current
• Managed the analysis of Electronic Health Records (EHR) using SQL for data querying and manipulation, Python with Pandas and NumPy for statistical analysis.
• Integrated data from multiple sources into Power BI, including electronic health records
(EHR), patient demographics, and medical history, to create a comprehensive view of patient health and treatment outcomes.
• Implemented DAX measures to calculate key performance indicators (KPIs) such as treatment effectiveness, patient readmission rates, and preventive care adherence, enabling stakeholders to track and monitor healthcare metrics.
• Assisted in machine learning algorithms to predict patient outcomes, such as readmission rates, treatment effectiveness, and risk of complications, based on historical patient data and clinical variables.
• Created visualizations and graphical displays of healthcare data using SAS procedures such as PROC GPLOT enabling stakeholders to explore trends, patterns, and relationships in the data.
• Stored large volumes of healthcare data in the Data Warehouse, using Snowflake's cloud-based architecture for scalable and efficient data storage. Data Analyst HCL Tech, India Sept 2019 – Dec 2021
• Implemented targeted marketing campaigns based on segmentation analysis, resulting in a 15% increase in conversion rates by delivering tailored messaging and offers to specific customer segments.
• Created trend lines, trend charts, and time-series visualizations in Tableau to analyze trends and patterns in customer behavior, campaign performance, and market dynamics over time.
• Utilized AWS Cost Explorer and AWS Budgets to monitor and optimize costs associated with data storage, computing resources, and machine learning services, ensuring cost- effectiveness, and maximizing ROI on AWS investments.
• Used Python libraries such as Pandas and NumPy to preprocess and clean customer data, and other datasets for analysis, ensuring data quality and consistency.
• Employed SQL queries to extract relevant data from databases, including customer information, campaign performance metrics, and sales data.
• Created line charts using Matplotlib to visualize trends over time, such as changes in customer engagement metrics or campaign performance metrics.
• Utilized Excel's pivot tables to summarize and analyze large datasets, enabling dynamic analysis and exploration of data by summarizing it in various ways based on user- defined criteria.
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