Data Analyst Supply Chain

Mohammed Danish

Data Analyst

704-***-**** **************@*****.*** LinkedIn

Professional Summary

• Data Analyst with 4+ years of experience in data analytics across finance, marketing and supply chain domains.

• Skilled in SQL, Python, Tableau, Power BI, and Excel for data analysis, reporting, and visualization.

• Proficient in building interactive dashboards, automating ETL pipelines, and real-time reporting tools.

• Experienced with cloud platforms including AWS, Azure, and Google Cloud utilizing Redshift, Snowflake, Big Query, and Synapse Analytics for scalable data solutions.

• Strong knowledge of statistical analysis and A/B testing for data-driven decision making.

• Hands-on with machine learning techniques including time series forecasting (LSTM, Prophet, ARIMA).

• Proven ability to work cross-functionally with business, product, and engineering teams Work Experience

State Street May 2024 – Present

Data Analyst (contract) United States

• Developed and optimized Tableau dashboards to track financial KPIs, portfolio performance, and risk assessment, improving decision-making efficiency by 40%.

• Designed ETL pipelines using Apache Airflow, AWS Glue, and Redshift, ensuring seamless integration of financial datasets across multiple sources.

• Automated data validation and quality checks using SQLAlchemy and Python, reducing manual data inconsistencies by 35%.

• Implemented A/B testing strategies using Chi-Square, T-tests, and Bayesian methods, leading to a 15% improvement in investment strategy performance.

• Integrated Snowflake and AWS S3 with the firm’s data warehouse, enabling real-time financial data access and accelerating report generation by 50%.

• Leveraged LSTM and Prophet models for time-series forecasting, increasing the accuracy of risk and revenue projections by 20%.

• Standardized and optimized SQL queries for large-scale financial datasets, reducing query execution time by 45% and improving system efficiency.

• Developed and deployed a Streamlit-based interactive reporting tool, allowing real-time access to financial insights for cross-functional teams.

• Built Power BI dashboards to track operational KPIs such as inventory turnover, order cycle time, and on-time delivery rates, improving visibility for the operations team.

• Automated Excel-based reporting using Power Query and VBA Macros, cutting down manual report generation time by 50%.

Cognizant Technology Solutions October 2020 – August 2023 Programmer Analyst India

• Designed and built interactive dashboards in Power BI, Looker, and Excel (Pivot Tables, Power Query) to track customer acquisition, churn rates, and campaign ROI, leading to a 28% increase in marketing efficiency.

• Developed customer segmentation models using K-Means clustering and Decision Trees, enhancing targeted marketing campaigns and increasing conversion rates by 12%.

• Conducted A/B testing to evaluate landing page and UX changes, applying T-tests and Chi-Square tests, which improved conversion rates by 18%.

• Created real-time ETL pipelines using AWS Glue, Lambda, and Redshift, enabling data ingestion from multiple sources such as MySQL, Oracle, and AWS Kinesis.

• Designed marketing attribution models to identify high-performing channels and optimize budget allocation, increasing marketing ROI by 15%.

• Built churn prediction and retention scoring models using Python, feature engineering, and logistic regression, improving targeting accuracy by 25%.

• Led data migration projects from on-premises databases to AWS cloud, successfully transferring over 50TB of data while maintaining 99.9% data integrity.

• Collaborated with the marketing and product teams to analyze customer lifecycle behavior and improve retention strategies.

• Conducted time series forecasting using Prophet and ARIMA, achieving 15% higher accuracy in revenue predictions.

• Optimized SQL stored procedures for large transactional datasets, reducing execution time by 40% and improving report refresh speeds.

Skills

Programming Languages: Python, R, SQL, JavaScript, C, Ruby, HTML, CSS. Databases: Snowflake, MySQL, PostgreSQL, Oracle, MongoDB, Redshift, SQL Server. Data Visualization: Tableau, Power BI, Looker, Matplotlib, Seaborn, Plotly. Machine Learning: Scikit-learn, TensorFlow, PyTorch, Azure ML, AWS Bedrock,Time Series Forecasting

(Prophet, LSTM, ARIMA).

Big Data & Cloud Technologies: AWS (S3, Redshift, Glue, Lambda), Azure (Databricks, Synapse Analytics, Data Factory, CosmosDB), Google Cloud (BigQuery, Cloud Functions). ETL & Data Engineering: Apache Airflow, DBT, Azure Data Factory, SSIS, Alteryx, PySpark, Kafka, CDC Pipelines.

Experimentation & Analytics: A/B Testing, Chi-Square Tests, T-Tests, Hypothesis Testing, Statistical Analysis, Feature Engineering.

Development & Version Control: Git, GitHub, JIRA, Streamlit, Flask. Other Tools & Frameworks: Excel (VLOOKUP, Pivot Tables, Macros), Pandas, NumPy, Power Query. Operating Systems: Windows, Linux.

Education

University of North Carolina at Charlotte August 2023 – December 2024 Master of Science in Computer Science Charlotte, NC Projects

Supply Chain Optimization Dashboard using Tableau

• Designed an interactive Tableau dashboard supported by SQL queries and Excel-based preprocessing to monitor key supply chain metrics including lead time, shipping delays, and inventory demand.

• Extracted and transformed logistics and warehouse data using SQL and Excel functions, enabling visibility into operational bottlenecks and driving improvements in delivery performance. Campaign Performance Dashboard for Customer Acquisition

• Designed a Power BI dashboard to track multi-channel marketing campaign performance across acquisition, engagement, and conversion KPIs.

• Used Excel and SQL to clean and transform campaign data from email, paid ads, and social media sources.

• Analyzed trends in customer acquisition cost (CAC), conversion rates, and ROI to guide budget reallocation and improve campaign efficiency by 18%.

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