Data Analyst Power Bi

KARTHICK SRIRAM MANIMARAN

*********.*@************.*** 857-***-**** Boston,MA LinkedIn

EXPERIENCE

Data Analyst, Northeastern University, Boston. Nov 2024 - Apr 2025

●Conducted quantitative and qualitative analyses using SQL, Excel, and Power BI to support strategic decisions, resulting in improved accuracy in forecasting and budgeting across departments.

●Partnered with cross-functional teams to assess and optimize internal workflows, identifying process inefficiencies and recommending improvements that enhanced operational efficiency by 15%.

●Developed interactive dashboards and automated KPI reports in Power BI, enabling real-time performance monitoring and driving more informed decision-making at the leadership level.

●Led small-to-medium scale projects, ensuring alignment with business priorities while delivering key milestones ahead of deadlines by streamlining team coordination and task tracking.

●Extracted and analyzed performance data using advanced Excel functions (PivotTables, VLOOKUP, Power Query) to produce actionable insights that informed operations and resource planning.

Admissions Assistant, Northeastern University, Boston. Nov 2024 - May 2025

●Managed and streamlined communication with hundreds of prospective students using Salesforce CRM, ensuring timely follow-ups, maintaining engagement, and boosting inquiry-to-application conversion rates.

●Resolved complex applicant inquiries using Five9 within Salesforce, reducing average response time and significantly enhancing the overall applicant experience.

●Generated and analyzed admissions data reports to identify applicant trends, behavioral patterns, and campaign performance, directly informing outreach strategies and optimizing funnel efficiency.

●Advised and guided prospective students through application requirements, scholarship opportunities, and campus life—building trust and ensuring a personalized and informative admissions journey.

●Collaborated with the admissions operations team to audit CRM workflows, improve case resolution logic, and implement new tracking procedures—resulting in improved data quality and reporting accuracy.

Business Data Analyst, Epidaurus Corporate Solutions, Chennai, India Mar 2021 - May 2023

●Collaborated with stakeholders across business units to define performance metrics, resulting in the development of analytical models that improved scenario planning and trend forecasting.

●Facilitated cross-functional workshops to gather business requirements and align teams on process improvement goals, leading to better stakeholder engagement and reduced feedback cycles.

●Applied operations research techniques (e.g., cost-benefit analysis, root cause analysis) to evaluate operational issues, reducing process failure recurrence and driving continuous improvement.

●Mapped current-state and future-state process flows, identifying gaps and proposing scalable automation opportunities that supported digital transformation initiatives.

●Streamlined recurring reporting processes by implementing Excel macros and business intelligence tools, reducing manual effort and cycle time by over 30%.

PROJECTS

Heart Disease Prediction using various ML and DL algorithms. Dec 2024

●Built and evaluated multiple predictive models using Logistic Regression, Random Forest, and Deep Neural Networks to classify risk of heart disease on a dataset of 2,000+ patient records.

●Performed data cleaning, feature selection, and hyperparameter tuning using GridSearchCV and Keras to optimize model performance.

●Achieved a 92% model accuracy, selecting a fine-tuned Random Forest as the final model to provide clinical decision support for early heart disease detection.

Tropical Cyclones: The Most Destructive Weather Phenomenon? - Tableau Dashboard Dec 2024

●Collected and merged multi-source geospatial data on tropical cyclones spanning over 20 years, applying preprocessing techniques in Excel and Python (Pandas).

●Designed multiple interactive visualizations in Tableau, showcasing storm intensity, economic impact, and regional vulnerability.

●Delivered a comprehensive dashboard used to identify high-risk zones and inform climate response strategies in academic discussions.

EEG Classification Model Using LSTM-CNN Model Feb 2024

●Developed a hybrid LSTM-CNN neural network in TensorFlow to classify EEG signals from a medical dataset of 11,500+ brainwave sequences for epilepsy detection.

●Applied signal preprocessing, windowing, and feature engineering to extract critical seizure indicators from temporal brain activity data.

●Achieved 87% classification accuracy, contributing to a proof-of-concept model for real-time neurological diagnosis support systems.

Customer Segmentation using RFM Analysis Feb 2024

●Conducted Recency, Frequency, Monetary (RFM) analysis on a 10,000+ customer dataset to segment consumers based on purchasing behavior using Python and Excel.

●Identified key segments (e.g., high-value, at-risk) and recommended personalized marketing strategies to enhance retention and lifetime value.

●Delivered insights through Power BI visualizations, enabling data-driven decision-making for campaign targeting.

Hack-overflow – Hackathon: Patient Data Retrieval System Sep 2022

●Designed and implemented a normalized MySQL database schema to manage patient records for a hospital use case under time constraints.

●Built an integrated backend system using SQL joins and indexing to support real-time querying and retrieval of patient medical histories.

●Enabled seamless, secure access to 1,000+ patient records, streamlining clinical workflows and improving patient care efficiency.

EDUCATION

Northeastern University, Boston, United States May 2025

Master of Science in Data Analytics Engineering

Relevant Coursework: Foundation of Data Analytics Engineering, Computation and Visualization for Analytics, Data Management for Analytics, Data Mining

Anna University, Chennai, India May 2023

Bachelor of Engineering in Computer Science and Engineering

SKILLS

Technical Skills: Python, SQL, R, C, Microsoft Excel, Power BI, Machine Learning, Big Data Handling, Data Mining, Data Visualization, Data Analysis, Data Science, and Business Analytics.

Database/Tools: Tableau, MYSQL, Microsoft Office 365, Git

Soft Skills: Communication skills, Problem Solving, Conflict Management, Critical Thinking, Adaptability, Attention-to-detail.

Certifications: Google Cloud - Architecting with Google Compute Engine Specialization

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