SREELAKSHMI BALAKRISHNAN

Tech-savvy innovator with hands-on experience in emerging technologies and passion for continuous improvement. Skilled in identifying opportunities for technological enhancements and implementing effective solutions. Adept at leveraging new tools and methods to solve problems and enhance productivity. Excels in adapting to fast-paced environments and driving technological advancements.

Six Sigma White Belt

SQL (Intermediate)

• Reduced organizational operating costs by 30% by streamlining processes.
• Client Interface - Worked in close collaboration with clients, providing accounting, payroll and taxation advice.
• Consumer Research - Effectively executed new marketing outlines based on market research data collected to reflect consumer interest on both tactical and strategic levels.

Relocation Flexibility: Open to opportunities, bringing a multicultural perspective and readiness to thrive in dynamic environments.

Languages: Fluent in English and familiar with communication standards across international business settings.
Professional Development: Actively pursuing certifications and advanced training in business analytics, ETL frameworks, and data visualization to expand technical depth.
Mentorship & Collaboration: Passionate about team development—trained junior analysts in SQL tuning, dashboard design, and documentation practices.
Portfolio Projects: Demonstrated experience in client onboarding optimization, grant compliance reporting, and KPI dashboard development, with live visualizations available on Tableau Public.
Networking & Leadership: Engaged in cross-functional workshops, UAT cycles, and strategy meetings with senior stakeholders; focused on aligning analytics with strategic goals.
Interests: Enthusiastic about transforming processes with technology, leading impact-driven analytics initiatives, and collaborating on global data solutions.

📦 Predictive Analytics in Supply Chain Optimization — Dell Technologies

This project focused on applying advanced predictive analytical techniques to enhance supply chain operations for electronic units at Dell Technologies.

🔍 Objective
To forecast inventory requirements with higher accuracy and streamline stock management by reducing excess inventory and preventing shortages.

📈 Approach

• Developed a predictive model to analyze historical demand data and procurement cycles.
• Applied statistical and machine learning techniques to fine-tune forecast accuracy for multiple product categories.
• Integrated model outputs into supply chain planning systems to support real-time decision-making.

🚀 Outcomes

• Increased capacity in forecasting precision, leading to more informed procurement planning.
• Realized operational efficiencies by minimizing overstock scenarios and optimizing warehouse utilization.
• Delivered insights that empowered strategic sourcing decisions and improved agility in inventory replenishment.

🧠 Impact
This analytical approach supported Dell’s goals in maintaining lean inventory levels while ensuring product availability. It became a vital asset for balancing cost and customer satisfaction across supply chain operations.

🚗🚙🛻 Electric Vehicle Data Analysis
Designed and developed an interactive Tableau dashboard analyzing 150,000+ electric vehicle records to uncover adoption patterns and market dynamics.

🔧 Key Contributions

• 🧼 SQL-driven data cleaning: Ensured high data integrity by standardizing variables and transforming inconsistent formats.
• 🧭 Strategic filters: Enabled dynamic filtering by model year, state, and fuel type, allowing stakeholders to perform tailored analyses.
• 📊 CAFV insights: Visualized Clean Alternative Fuel Vehicle (CAFV) eligibility data to support data-backed policy decisions and promote cleaner transportation.

💡 Impact
This analysis empowered decision-makers with a robust tool to forecast EV trends, evaluate regional adoption rates, and strengthen clean energy initiatives through actionable insights.

💳 Credit Card Fraud Detection 

This project focused on building a robust machine learning pipeline to detect fraudulent credit card transactions with maximum precision and minimal false positives.

🧠 Objective
To accurately identify 100% of fraudulent activities while reducing incorrect fraud classifications — a crucial balance in fraud analytics.

🔍 Project Scope

• Modeled historical transaction data labeled for confirmed fraud cases.
• Performed data cleansing and preprocessing, including normalization and outlier handling.
• Transformed feature space using Principal Component Analysis (PCA) for dimensionality reduction and enhanced anomaly detection.

⚙️ Techniques Implemented

• Local Outlier Factor (LOF) and Isolation Forest algorithms to identify suspicious patterns and anomalies.
• Evaluated model performance using precision-recall tradeoffs and confusion matrices to fine-tune results.

📊 Outcome
The resulting model demonstrated a high detection rate of fraudulent transactions, offering valuable insights into behavioral deviations and risk profiles. This project highlighted the power of unsupervised learning methods for anomaly detection in real-world financial datasets

💼 Banking Data Portfolio Analytics Dashboard — Tableau Public

This project aimed to deliver a robust and interactive dashboard for real-time monitoring of bank loan performance and portfolio trends.

📊 Dashboard Features

• Tracked $435.8M in funded loans and $473.1M in received payments, enabling end-to-end visibility into loan activities.
• Designed filters for verification status, loan grade, and loan purpose to facilitate customized portfolio reviews.

🗺️ Visual Insights Delivered

• Geographic distribution maps pinpointed regional loan activity hotspots.
• Temporal trend analysis revealed market momentum across loan durations and funding cycles.
• Demographic breakdowns identified that 70.35% of loans were 36-month terms, with $253.8M allocated to debt consolidation.

📌 Executive-Level KPIs

• Showcased metrics like 11.7% average interest rate and 13.3% Debt-to-Income (DTI).
• Monthly trend visualizations reported a notable 15.8% MoM growth in received payments, informing strategic decisions.

🌟 Impact
This dashboard empowered stakeholders with critical loan performance metrics, facilitating faster decisions in credit risk management, portfolio planning, and growth strategy alignment.

📈 Commercial Portfolio Performance Analysis Dashboard — Tableau Public

This project delivered a high-impact Tableau dashboard for analyzing sales performance and identifying strategic growth opportunities across product portfolios.

🔍 Key Features

• Built profitability-growth quadrant visualizations to pinpoint $1.16M in high-performing product categories and uncover 8700%+ growth potential, driving resource optimization.
• Enabled dynamic, interactive filtering across sales and margin dimensions, categorizing products into Winners, Losers, and Opportunity Areas for clearer decision-making.
• Combined scatter plots and metrics tables to highlight critical product KPIs, including 35% profit margins, $638K+ in sales, and 1200%+ growth rates.

🚀 Impact
Empowered executive teams with instantly digestible insights to steer product strategy, reallocate investments, and focus on growth-driving segments—transforming raw metrics into decisive business action.