Data Analyst Analytics

SHASHANK RALLAPALLI

Boston, MA, USA • +1-617-***-**** • ********.****@*****.*** • LinkedIn • GitHub • Tableau SUMMARY

• Accomplished Data enthusiast with 3.4 years of experience in implementing advanced machine learning algorithms and predictive models to enhance business operations. Proven success in automating processes, reducing manual tasks by up to 50%, and achieving high accuracy in forecasting and anomaly detection.

• Expertise in developing analytical dashboards, resulting in significant improvements in sales, retention, and customer satisfaction.

• Proficient in Python, SQL, Qlik Sense, Tableau, and Power BI, with a strong background in data warehousing, ETL processes, and statistical analysis. Demonstrated ability to deliver actionable insights and drive strategic improvements, contributing to cost savings and operational efficiency. EDUCATION

Master of Science in Analytics & Data Science, Northeastern University, Boston, MA, USA Apr - 2024 PROFESSIONAL EXPERIENCE

Data Scientist, BMW of North America LLC, USA Apr 2023 – Sept 2023

• Leveraged Python for data manipulation, statistical analysis, and visualization, utilizing libraries such as Pandas, NumPy, and Matplotlib to uncover trends and insights that informed strategic business initiatives.

• Conducted extensive data analysis using SQL to extract, clean, and transform large datasets, optimizing queries and enhancing data retrieval processes which supported data-driven decision-making

• Designed an analytical dashboard in Qlik sense integrating retail and wholesale count data, reducing data recording errors and VIN discrepancies by 70%.

• Utilized clustering algorithms, such as K-means and Hierarchical Clustering, to segment customers based on purchasing behavior and demographics which allowed the marketing team to implement targeted pricing strategies, increasing sales conversion rates by 30%.

• Utilized advanced Excel functions like VLOOKUP, pivot and VBA scripting to automate data processing tasks, create dynamic financial models, and generate comprehensive reports that streamlined workflow and improved reporting accuracy.

• Developed time series forecasting models using ARIMA and Prophet to predict monthly sales trends. Incorporated variables such as historical sales data, seasonal patterns, and economic indicators, achieving a 90% accuracy rate in sales predictions.

• Engaged with key stakeholders to gather requirements, present data insights, and provide actionable recommendations, ensuring alignment with business objectives and facilitating informed decision-making.

Data Analyst, Honeywell Technology Solutions, India Jan 2021 - Dec 2021

• Regularly conducted meetings with stakeholders to gather requirements, provide updates, and ensure alignment on business objectives. Created comprehensive documentation including business requirements, process flow diagrams, and user manuals to support project deliverables.

• Identified inefficiencies in the travel and expenses process, recommending actionable improvements that led to a 10% reduction in unnecessary expenses.

• Implemented a predictive model using linear regression to accurately forecast expenses for the upcoming financial year with 82% accuracy, facilitating effective budget planning and expenditure reduction strategies.

• Automated data manipulation and expense forecasting processes using Alteryx and its machine learning capabilities (Auto ML), resulting in a reduction of 20 manual work hours per week.

• Developed an analytical dashboard in Tableau to analyze the company's travel and expenses data, identifying over 10% of unnecessary expenses and projecting potential savings of $20K. Optimized Tableau dashboard operational time to 2-8 seconds by enhancing data processing and visualization techniques.

• Conducted in-depth data analysis using various statistical methods, such as hypothesis testing and regression analysis, to uncover trends, patterns, and insights that informed business decisions and strategies.

• Utilized SQL for querying databases, performing complex joins, aggregations, and data transformations to support reporting and analytical requirements, ensuring data accuracy and consistency across various business applications.

• Optimized database performance through indexing, partitioning, and query optimization using SQL techniques, leading to a 35% reduction in data retrieval times.

• Developed and maintained data warehousing solutions, integrating data from multiple sources to create a centralized repository which enabled more efficient data retrieval and reporting, reducing query times by 40%. Data Analyst, Tech Mahindra (Lear Corporation & Honeywell), India Mar 2018 - Jan 2021

• Developed live Power BI reports for continuous monitoring of plant functionality and efficiency, leading to a significant improvement in plant efficiency to 96%.

• Applied advanced machine learning techniques and data modeling in Python and SQL, ensuring the integrity and efficiency of data structures for improved predictive accuracy.

• Created real-time predictive models for continuous monitoring of plant functionality, contributing to a 16% increase in overall plant efficiency.

• Designed and implemented data models and data warehousing solutions, improving data accessibility and reliability to support large-scale data analysis and reporting needs.

• Enhanced decision-making with a real-time alert system for business leaders using Power BI and Python, reducing issue resolution delays by 40%.

• Analyzed complex historical data using statistical methods to identify four least-performing plants with overall efficiency below 80%, and reported findings to business stakeholders.

• Leveraged SQL for database management and ETL processes, optimizing data flow and ensuring data quality in data warehousing solutions.

• Presented actionable insights from data analysis and root cause analysis to drive strategic improvements in plant operations, aligning with business goals. SKILLS & OTHER

Methodologies: Agile

Language: Python, SQL, Java.

Packages: Pandas, NumPy, MatplotLib, SciPy, Scikit-Learn, SeaBorn, PyTorch, TensorFlow, ggplot2, Plotly, Keras, LangChain. IDES: Visual Studio Code, Jupyter Notebook, PyCharm. Database: SQL Server, MongoDB, Azure Data Lake, Data Warehousing, Amazon Redshift, Amazon DynamoDB. Data Analytics Skills: Data Manipulation, Predictive Analysis, Data Cleaning, Data Mining, Data Visualization, Statistical Modeling, Exploratory Data Analysis. Cloud: Snowflake, Docker, Kubernetes, AWS (Redshift, Athena, Glue, Sage Maker, S3), Azure (Databricks, dbt). Other Skills: A/B Testing, Hypothesis testing, Databricks, Snowflake, Big Query, Apache Airflow, Critical Thinking, Communication Skills, Presentation Skills, Problem-Solving. Version Control Tools: Git, GitHub

Operating Systems: Windows

PROJECT

Rapid Text-to-SQL Large language Model (LLM) Chatbot Project

• Unlocking Insights from University Data Leveraged Lang chain & Open Ai’s GPT-3.5 Turbo for real-time interaction with a PostgreSQL database CERTIFICATIONS

• Microsoft Certified Power BI Data Analyst Associate - June 2024 ACHIEVEMENTS

• Built interactive dashboards employing predictive modeling techniques to analyze discrepancies between receivables and accounts payable, leading to a 10% decrease in financial errors and enhanced financial management practices.

• Assisted business in clearing approximately $1.2M of overdue payments to various vendors by providing clear insights from forecasting and Tableau reports.

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