NENAVATH SAI SRIDHAR

Email: ad4idl@r.postjobfree.com

LinkedIn:linkedin.com/in/sai-sridhar-nenavath-855207214

Summary:

Experienced Data Analyst with around 2 years of experience, possessing a strong background in developing data pipelines, ETL processes, and implementing data governance measures. Proficient in extracting, transforming, and loading large datasets from diverse sources using SQL and Python. Skilled in utilizing data visualization and analysis tools such as Power BI and Tableau. Demonstrated expertise in cloud platforms, particularly AWS, with a focus on security best practices. Experienced in collaborating with cross-functional teams to deliver end-to-end data solutions and effectively communicate technical concepts to non-technical stakeholders. My proficiency in using Python, SQL, and big data technologies such as Databricks, Spark, and Power BI.

I'm a graduate student with a Master’s in Data Science. And I’m always keen to learn new technologies and tools.

EDUCATION:

University of Maryland, Baltimore County (UMBC)

Master of Science in DATA SCIENCE

Duration: Graduated in 2023

GPA: 3.5

Little Flower Degree College, Hyderabad

Bachelor of Science in Computer Science.

Duration: Graduated in 2021

GPA: 3.7

TECHNICAL SKILLS:

Languages

Python, R, C/C++

Frameworks

Django, Flask

Python Packages

NumPy, Pandas, Matplotlib, SciPy

Version Control Tools-

GitHub, SVN, GitLab

Management Tools

SVN, Git

Databases

MySQL, SQL Server

Operating Systems

Unix, Linux, Windows, and Mac OS

Statistical Analysis

Hypothesis testing, Regression analysis, Excel, SPSS.

Big Data Technologies

Hadoop, Spark, Databricks, AWS, Azure

PROFESSIONAL EXPERIENCE:

Tricode Info Solutions June 2020 – Dec 2021

Data Analyst

Demonstrated ability to analyze complex datasets, extract insights, and present findings to support business decision-making processes.

Proficient in applying statistical methods such as hypothesis testing, regression analysis, and correlation analysis to derive actionable insights from data.

Proficient in leveraging Python for data manipulation, visualization, statistical analysis, machine learning, web scraping, and automation tasks, enhancing efficiency and effectiveness in data analysis workflows.

Highly skilled in programming languages such as Python, R, and SQL, with extensive experience in querying, manipulating, and managing data in relational databases.

Experience in creating clear and informative data visualizations using tools like Tableau, Power BI, or Matplotlib to communicate complex concepts to stakeholders.

Possess strong data cleaning and preprocessing skills, including handling missing values, and outliers, and ensuring data quality and integrity for analysis.

Actively engaged in continuous learning and professional development activities, including attending conferences, obtaining certifications, and staying updated with emerging trends and technologies data analysis.

Strong analytical and problem-solving skills to tackle complex data challenges, identify root causes of issues, and develop innovative solutions to drive business outcomes.

Demonstrated success in delivering high-impact data analysis projects, achieving measurable business outcomes, and driving organizational growth and innovation.

ACADEMIC PROJECTS:

Walmart Stores Sales Forecasting

In this Project, I employed advanced data science methodologies, including time series analysis, machine learning, and predictive modeling, to develop the sales forecasting model. Python was the primary programming language for data preprocessing, feature selection, and model development.

Designed, implemented, and optimized end-to-end ETL pipelines for efficient data management using Python, Shell scripting, and real-time integration.

Utilized Ansible for automation of specific tasks within the project workflow.

Heart Disease analysis and prediction

Developed a predictive model for heart disease risk using a Kaggle dataset (1025 entries).

Focused on addressing the global health issue of heart disease, a leading cause of 17.9 million deaths annually, often linked to lifestyle factors.

Proficiently utilized Python for data preprocessing, feature engineering, and machine learning tasks.

Created interactive visualizations with Tableau and Power BI to effectively communicate complex trends and patterns in heart disease risk factors.

Employed Shell scripting for specific data preprocessing tasks, showcasing practical skills.

Acknowledged the limitation of a small dataset and proposed future improvements like collecting more diverse data and exploring familial heart disease risk factors.

Maryland Vehicle Crashes Analysis using PySpark

Analyzed Maryland's 2020 vehicle crash data to identify key factors influencing accidents, aiming to improve road safety.

Utilized PySpark for efficient processing of large crash datasets.

Implemented data preprocessing techniques to enhance data quality.

Conducted statistical analysis and visualizations to uncover trends and risk factors.

Generated actionable insights for enhancing road safety strategies.

Utilized Shell scripting and JavaScript for data preprocessing and interactive visualizations.

Demonstrated expertise in PySpark, data engineering, analysis, and visualization.

Emphasizes the use of data-driven approaches to address transportation and safety challenges.

CERTIFICATIONS:

Data Analyst Professional Certification by IBM

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