Data Analyst Engineer

***************@*****.***

SENA SAIRAM

contact: 919-***-****

KATRAGADDA

Cary, NC,27519

PROFESSIONAL SUMMARY

Detail-oriented and analytical Data Analyst with 4 years of experience working in diverse

industries, including IT consulting and software solutions. Skilled in data collection,

cleaning, and visualization, as well as proficiency in statistical analysis and machine

learning algorithms. Proven track record of enhancing business decision-making through

the effective use of data and tools such as Python, SQL, Excel, and Tableau. Strong

problem-solving abilities with a commitment to continuous learning and professional

growth.

PROFESSIONAL EXPERIENCE

DATA ENGINEER

Rave Systems Inc. – Virginia, USA Inc [Virginia] August 2023 - Present

Conducted data analysis to identify business trends, patterns, and insights for

clients across various industries including retail and finance.

Cleaned, processed, and transformed large datasets using SQL and Python to

ensure data integrity and consistency for reporting.

Developed and maintained interactive dashboards and reports in Tableau to

visualize key performance indicators (KPIs) and present data insights to

stakeholders.

Worked closely with cross-functional teams to develop data-driven strategies

that improved operational efficiency by 15%.

Created detailed data reports, including descriptive statistics and data

visualizations, to guide decision-making for senior management.

Automated data collection and reporting processes, reducing the time for

generating weekly reports by 40%.

Conducted A/B testing and predictive modeling for client campaigns,

improving conversion rates by 10%.

KEY ACHIEVEMENTS

Improved data accuracy and reporting efficiency, reducing reporting

time from 3 days to 1 day.

Enhanced data quality by implementing data validation rules, reducing

data errors by 25%.

DATA ANALYST

Moonstone Infotech, [Hyderabad] October 2018 - April 2022

Managed large-scale data migration projects, ensuring

seamless integration across multiple databases.

Developed KPI dashboards that enabled executives to

make data-driven decisions, leading to a 15% boost in

revenue growth.

Conducted exploratory data analysis (EDA) to uncover patterns and

correlations, enhancing the company’s strategic planning.

Automated repetitive data processing tasks using Python scripts,

reducing manual efforts by 40%.

Led cross-functional workshops to educate stakeholders on data literacy

and best practices in analytics.

Created detailed reports and visualizations to communicate insights to

both technical and non-technical teams, improving transparency in

decision-making.

Implemented advanced statistical models to optimize marketing

campaigns, leading to a 10% increase in customer acquisition.

KEY ACHIEVEMENTS

Increased client retention by providing data insights that

helped optimize user experience, contributing to a 15%

increase in customer satisfaction scores.

Reduced the time spent on manual reporting by 35% through

the automation of recurring data queries and reports.

EDUCATION

BACHELORS OF COMPUTER SCIENCE

KL University 2015 - 2019

MASTERS IN DATA SCEINCE

Indiana Wesleyan university August 2022 - October 2024

PROJECTS

1. Data Visualization with R Studio

Utilized R Studio to analyze and visualize complex datasets.

Created interactive charts and dashboards to present data-

driven insights effectively.

Applied statistical techniques to extract meaningful

patterns.

2. Data Mining with Jupyter Notebook

Conducted data mining using Python and Jupyter Notebook to

uncover hidden patterns in large datasets.

Implemented data preprocessing techniques including cleaning,

normalization, and feature selection.

Utilized libraries such as Pandas and Scikit-learn for analysis and

predictive modeling.

3. Big Data Processing with Hadoop and Hive

Managed and processed large datasets using Hadoop Distributed

File System (HDFS).

Employed Hive for querying and analyzing data stored in Hadoop.

Optimized data workflows to improve query performance and

efficiency.

CERTIFICATIONS

Perform exploratory data analysis on retail data

with Python (Coursera)

Data Analysis with SQL: Inform a Business

Decision (Coursera)

AWS Certified Data Engineer - Associate (AWS)

TECHNICAL SKILLS

Data Analysis: Python (Pandas, NumPy), R, SQL, Excel (Advanced),

Power BI, Tableau

Data Cleaning & Transformation: ETL Processes, Data Wrangling

Statistical Analysis & Modeling: Regression Analysis, Hypothesis

Testing, Predictive Modeling

Databases: MySQL, PostgreSQL, Microsoft SQL Server

Tools & Software: Microsoft Excel, Jupyter Notebook, Google

Analytics, Tableau, Power BI, Git, Google BigQuery

Programming Languages: Python, SQL, R

Machine Learning: Experience with Algorithms, NLP Techniques,

and applying statistical approaches

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