Data Analyst Business Intelligence

Dinesh Chandra Midde Data Analyst

IL, USA +1-224-***-**** ******************@*****.***

SUMMARY

Data Analyst with over 3 years of experience in data analytics and business intelligence, specializing in leveraging data to drive business decisions and operational improvements. Skilled in customer analytics, predictive modeling, and NLP-based sentiment analysis, delivering actionable insights that enhance operational efficiency and customer satisfaction. Proficient in building interactive dashboards, optimizing ETL processes, and improving call center performance metrics. Experienced in integrating AI-powered solutions and collaborating with cross-functional teams to optimize business operations.

TECHNICAL SKILLS

Languages Python, R, SQL

Frameworks/Libraries Pandas, NumPy, Scikit-learn, BeautifulSoup, Selenium, NLTK, spaCy, TextBlob BI & Visualization Tools Power BI (DAX, Data Modeling), Tableau, Excel (Pivot Tables, VBA, Advanced Formulas) Databases SQL Server, MySQL, PostgreSQL, AWS Redshift, NoSQL, MongoDB ETL & Data Engineering SQL, Apache PySpark, Apache Spark, Airflow, AWS Glue, Pipeline Automation, Data Cleaning & Transformation Cloud Computing AWS (Redshift, S3, Lambda, Glue, EC2, IAM, VPC), Azure (Synapse, Blob Storage, VMs) Security & Compliance HIPAA, SOC 2, GDPR, AWS IAM, RBAC, Data Privacy Measures Build/Other Tools UML, MS Visio, Jupyter Notebook, Google Colab Version Control Tools Git, GitHub, Jira, Trello

IDEs PyCharm, Jupyter Notebook, VS Code, Spyder

Methodology SDLC, Agile, Waterfall, CRISP-DM

Operating Systems Windows, Linux

PROFESSIONAL EXPERIENCE

Charles Schwab, USA Jan 2024 – Current

Data Analyst

• Streamlined financial reporting workflows, reducing latency by 35%, by building automated ETL pipelines in AWS Glue and integrating multi- source datasets into Redshift using SQL and Python.

• Predicted churn risk with 82% accuracy using a Scikit-learn classification model, enabling client services to proactively engage high-risk customers and improve retention by 18%.

• Developed executive dashboards in Tableau, implementing advanced visualizations, parameters, and calculated fields to monitor KPIs such as AUM growth, trading patterns, and client engagement metrics across 5+ business units.

• Extracted market intelligence from competitor websites using Selenium and BeautifulSoup, automating data collection efforts that saved ~10 hours/week and informed quarterly strategy decisions.

• Analyzed customer sentiment via call transcripts using spaCy and TextBlob, uncovering service bottlenecks that drove a 12% improvement in CSAT scores.

• Collaborated in Agile sprints with product, BI, and compliance teams to translate analytical findings into product enhancements and operational improvements.

• Ensured compliance with HIPAA, GDPR, and SOC 2 regulations by implementing IAM/RBAC policies and anonymizing PII during all stages of data processing and reporting.

Intex Technologies India Mar 2021 – Jul 2022

Technical Data Analyst

• Analyzed large datasets from CRM, e-commerce platforms, and retail sales databases using SQL and Python (Pandas, NumPy) to extract actionable insights, contributing to an 18% market share increase in Tier II and III cities.

• Developed predictive analytics models using machine learning algorithms (Random Forest, XGBoost) to forecast product demand, optimizing inventory planning and reducing stock shortages by 30%.

• Data pipeline Automation for ETL processes, streamlining data ingestion and transformation, improving data accuracy and processing speed by 40%.

• Visualized dynamic Power BI and Tableau dashboards, visualizing sales performance, customer segmentation, and pricing strategies, enabling senior leadership to make faster, data-driven decisions.

• Carried out competitor analysis initiatives by leveraging web scraping tools (BeautifulSoup, Selenium) to track pricing, features, and market trends from Samsung, Xiaomi, and Realme, driving strategic product positioning.

• Implemented pricing optimization models using regression analysis and A/B testing, refining pricing strategies and leading to a 15% improvement in sales conversions.

Intex Technologies India Technical Data Analyst Intern Jun 2020 – Feb 2021

• Conducted end-to-end sentiment analysis on 100,000+ customer reviews using SQL, Python (Pandas, NumPy), and NLP (NLTK, VADER, TextBlob), leading to a 15% increase in customer satisfaction scores within six months.

• Built and optimized SQL queries and automated data pipelines to aggregate, clean, and structure multi-source customer feedback, improving data retrieval efficiency by 30% and reducing manual processing efforts.

• Developed interactive Power BI dashboards to visualize customer sentiment trends, enabling data-driven decision-making across product development, customer experience, and marketing teams.

• Implemented machine learning-driven predictive analytics models (Naïve Bayes, A/B testing, Churn Prediction) to classify sentiment, anticipate complaints, and optimize customer service, reducing return rates by 30%.

• Automated data extraction using Selenium and API integrations, streamlining data collection from e-commerce platforms and social media, leading to a 35% improvement in processing speed.

• Led the analysis of key product issues (battery performance, overheating, service delays), influencing design improvements and driving product enhancements that reduced negative feedback by 20%. EDUCATION

Master’s in Computer Engineering Arizona State University, AZ May 2024 Bachelors in Electronics and Communication Engineer SRM University, India May 2022

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