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Data Analyst

Minneapolis, MN
January 30, 2024

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Nithishreddy Kunta

Data Analyst

Email: / Mobile: +1-651-***-****


Highly motivated and results-oriented Data analyst with 4+ years of experience leveraging data insights to optimize operations, enhance efficiency, and drive strategic decision-making in highly competitive environments. Proven track record of exceeding targets through

• Data-driven problem solving: Identified hidden trends and patterns in complex datasets, leading to a 15% cost reduction and 25% improvement in data quality.

• Predictive power: Built and deployed a 90% accurate machine learning model, saving $100,000 in maintenance costs.

• Technical expertise: Proficient in Python, SQL, Tableau, Power BI, Hadoop, Spark, and machine learning techniques.

• Collaboration leadership: Successfully bridged the gap between data and action, partnering with cross-functional teams to implement data-driven initiatives.

• Data storytelling: Mastered the art of translating complex data into compelling narratives, influencing key decisions and driving customer satisfaction.

• Leader in data: Mentored junior analysts, ensuring knowledge sharing and fostering a data- driven culture within the organization.

• Strong communication skills: Presented actionable insights to stakeholders, influencing key decisions and improving customer satisfaction.


Programming Languages: Python (expert), R (intermediate) Data Visualization Tools: Tableau (expert), Power BI (expert) Database Management: SQL (expert), MySQL (expert), Hadoop (intermediate), Spark


Big Data Technologies: Hadoop, Spark (intermediate) Version Control: Git (expert)

Operating Systems: Windows (expert), Linux (intermediate) Data Analysis: Data cleaning, data preprocessing, machine learning, data mining, statistical analysis, hypothesis testing

Cloud Platforms: AWS (basic)


• Master of Computer Science, Concordia University, St. Paul, Minnesota Sep 2022- Dec 2023

• Bachelor of Computer Science, Osmania University, India Jul 2017- Oct 2020 PROFESSIONAL EXPERIENCE:

Extendime, Old Bridge, NJ Apr 2023 –Dec 2023

Data Analyst


• Designed and implemented a dynamic Tableau dashboard to track real-time operational metrics, enabling data-driven decision-making across departments.

• Streamlined data acquisition and cleaning processes using Python and SQL, boosting data quality by 25% and reducing analysis time by 20%.

• Built and deployed a machine learning model to predict equipment failures with 90% accuracy, preventing operational downtime and saving $100,000 in maintenance costs.

• Identified and analyzed sales trends, leading to a 10% increase in customer conversions through targeted marketing campaigns.

• Collaborated with product development teams to leverage data insights for product feature prioritization and optimization.

• Developed and delivered engaging data-driven presentations to senior management, influencing strategic decisions and resource allocation.

• Mentored junior analysts, promoting knowledge sharing and fostering a data-driven culture within the organization.

• Successfully migrated historical data from legacy systems to a modern data warehouse, ensuring data accessibility and future-proofing data infrastructure.

• Identified and documented data governance best practices, improving data integrity and compliance with regulatory requirements.

• Developed and implemented automated data pipelines to streamline data flow and reduce manual workload.

Environment: Python, MySQL, Spyder IDE, Jupyter Notebook, Tableau, Power BI, Matplotlib, Sea born, Plotly, PostgreSQL, Git, GitHub, Anaconda

Datavail Info Tech, Hyderabad, India July 2019 – August 2022 Data Analyst


• Optimized database queries in MySQL, improving response times by 30% and enhancing operational efficiency.

• Conducted hypothesis testing and statistical analysis to determine the effectiveness of marketing campaigns, leading to a 5% increase in ROI.

• Implemented Power BI dashboards to visualize key performance indicators for marketing and sales teams, improving team alignment and accountability.

• Leveraged data mining techniques to uncover hidden customer segments, informing targeted marketing efforts and personalized customer experiences.

• Supported the implementation of a customer relationship management (CRM) system, streamlining data management and improving customer service.

• Collaborated with IT teams to troubleshoot data integration issues and ensure data quality across the organization.

• Automated data reports using Python scripts, freeing up analyst time for deeper data analysis and insights generation.

• Presented data-driven insights to leadership, providing a data-backed foundation for strategic decision-making.

• Analyzed customer feedback data to identify pain points and inform product improvement initiatives.

• Successfully onboarded new data analysts, providing training and support for continuous development of the data analytics team.

Environment: Python, MySQL, Spyder IDE, Jupyter Notebook, Tableau, Power BI, Matplotlib, Sea born, Plotly, PostgreSQL, Git, GitHub, Anaconda.

Personal Projects:

SCADA for Transformer Monitoring

• Designed and implemented a web-based SCADA system for real-time monitoring of transformer health and performance.

• Integrated sensors and data acquisition systems to collect voltage, current, temperature, and other critical metrics.

• Developed custom algorithms to analyze data and identify early signs of potential transformer failures.

• Implemented automated email alerts to notify maintenance teams of potential issues, minimizing downtime and preventing catastrophic failures.

• Achieved a 20% reduction in downtime and a 10% decrease in operational costs through early detection and proactive maintenance.

Wind Energy System with Variable-Speed SOFC

• Created a novel control system for a wind energy conversion system integrated with a solid oxide fuel cell (SOFC).

• Optimized SOFC operation for variable wind speeds by dynamically adjusting fuel input and power output.

• Increased energy conversion efficiency by 20% through improved load matching and heat utilization.

• Reduced transient response time by 50% with a custom control algorithm, maintaining system stability during fluctuating wind conditions.

• Mitigated grid disturbances by dynamically adjusting power output, ensuring grid stability and compliance with regulations.

Loan Defaulter Prediction

• Built a machine learning model using logistic regression to predict loan defaulters with 95% accuracy.

• Implemented data cleaning and feature engineering techniques to prepare the training data set.

• Conducted exploratory data analysis to identify key factors influencing loan default risk.

• Developed a user-friendly web application for lenders to assess loan defaulters.

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