Reshmika Reddy

About Reshmika Reddy

As a Data Analyst with around 4 years of experience, I specialize in translating complex datasets into actionable insights that drive business performance. My expertise spans SQL, Python, R, and statistical modeling, paired with advanced data visualization tools like Tableau, Power BI, and Excel. I’ve delivered predictive models, customer segmentation strategies, and performance dashboards that enhanced decision-making and boosted KPIs—such as improving cross-sell rates by 30% and reducing reporting errors by 30%.I’m proficient in cloud platforms like AWS, Azure, and GCP, and skilled in building scalable ETL workflows and automating data pipelines. My background includes working with large datasets (millions of records), applying machine learning techniques, and supporting executive strategy through real-time analytics. I thrive in Agile environments and enjoy collaborating cross-functionally to solve tough problems with data.Let’s connect if you\'re interested in data-driven transformation, scalable analytics, or enhancing decision intelligence through storytelling with data.

Experience

1. Data Analyst

   DSW Designer Shoe Warehouse

   Jun 2024 — Present

   Collaborated with cross-functional teams to gather requirements and translate business needs into actionable insights, leveraging SAFe Agile methodologies and advanced analytical tools, resulting in a 15% improvement in project delivery.• Developed advanced predictive models for sales forecasting and market analysis across different product lines using SQL, Python, and statistical techniques, improving cross-selling opportunities by 30% and enabling data-driven resource allocation.• Performed customer segmentation using dimensionality reduction techniques, clustering, and data visualization techniques, identifying behavioral trends that increased conversion rates by 15% and supported personalized marketing strategies.• Designed dynamic and interactive dashboards in Tableau and Looker Studio, integrating datasets from 20+ sources for 50+ stakeholders to provide key performance indicators (KPIs) tracking and strategic insights for executive-level decision-making.• Streamlined preprocessing workflows by integrating advanced feature engineering and feature selection techniques, reducing data latency and enhancing overall system processing over 2 million records daily.• Executed comprehensive exploratory data analysis (EDA), root cause analysis, and data manipulation on complex datasets, identifying critical anomalies and trends that reduced reporting errors by 30%.

Education

• University of Illinois Chicago

  Master of Science - MS

  2022 — 2023