Data Analyst Power Bi

Monish Kamal Bathini

DATA ANALYST

TX, USA 732-***-**** ***********@*****.*** LinkedIn

SUMMARY

Detail-oriented and results-driven Data Analyst with 4 years of experience delivering actionable insights, real-time analytics, and data-driven business strategies across healthcare and fintech sectors. Skilled in leveraging Python, SQL, and BI tools to design end-to-end data solutions that align with stakeholder needs. Adept at transforming complex datasets into dynamic visualizations using Power BI and Tableau, and applying advanced analytics techniques, including natural language processing (NLP), to drive informed decision-making and business reviews.

SKILLS

Programming Languages:

Python (Pandas, NumPy, Seaborn, Matplotlib), R, SQL, Advanced Excel.

Data Analysis & Modeling:

Data Cleaning, Exploratory Data Analysis, Data Mining, KPI Design, Regression Techniques.

Data Visualization:

Power BI, Tableau, Jupyter Notebook, Advanced Excel (Pivot Tables, Macros, VLOOKUP), BI Tools.

Databases / NoSQL:

MySQL, PostgreSQL, Microsoft SQL Server, MongoDB, Data Structures, Database Optimization.

Advanced Analytics & Tools:

R, SAS, Minitab, Google Analytics, NLP, Descriptive & Inferential Statistics, Keras, PyTorch, TensorFlow, ML.

Methodologies:

SDLC, Agile, Waterfall, JAD Sessions, UAT, Sprint Planning, Business Analytics, QA Documentation.

Documentation:

User Stories, Regulatory Compliance, Prototyping, Compliant Tracking.

Project Management Tools:

Microsoft Office Suite (Excel, Word, PowerPoint), MS Teams, Google Workspace.

Soft Skills:

Communication (Verbal & Written), Team Collaboration, Presentation, Leadership, Decision-Making.

Analytical & Organizational Skills:

Problem-Solving, Critical Thinking, Attention to Detail, Time Management.

WORK EXPERIENCE

Data Analyst Optum, TX Jan 2024 –Present

Collaborated with multidisciplinary care teams and data engineers to conduct requirement gathering and Joint Application Development sessions, defining over 20 patient-centric KPIs, risk stratification rules, and clinical reporting thresholds for use in predictive care models.

Designed interactive and drill-through dashboards using Power BI and Advanced Excel (macros, pivot charts, nested formulas, and slicers), which enabled dynamic visualization of patient throughput, discharge timelines, and escalations, reducing reporting turnaround by 38%.

Executed complex exploratory data analysis on structured and unstructured clinical data using Python (Pandas, Seaborn) and SQL; engineered readmission scoring logic that increased care planning accuracy by 21% through pattern detection in biometric and treatment data.

Applied Minitab for statistical quality control and used Google Analytics to evaluate engagement with internal care portals; identified navigation bottlenecks and proposed UX/UI adjustments that improved portal usage among staff and clinicians by streamlining user flows.

Authored detailed process maps, early-stage wireframes, and prototype documentation using Microsoft Word, PowerPoint, and Google Workspace, aligning sprint deliverables with compliance standards, and supporting the QA team with audit-traceable visual workflows.

Led multiple User Acceptance Testing cycles for care coordination dashboards, preparing scripts, managing test environments, logging defects, and facilitating feedback loops to ensure stakeholder approval and functional correctness of the deployed features.

Data Analyst Deloitte, India May 2020 -Dec 2022

Conducted discovery workshops with credit analysts, legal teams, and IT architects to gather domain-specific business rules and regulatory requirements for fraud detection and credit risk modeling, translating them into scalable analytics specifications.

Engineered credit scoring models using R and SAS by applying logistic regression, variable binning, and ROC curve analysis on loan and repayment data; integrated output scores into eligibility logic that enabled policy restructuring for sub-prime retail segments.

Ingested and transformed multi-source transactional data (~15M/month) using Apache Spark and Hadoop (MapReduce, HDFS), reducing data preparation time by 41% and supporting risk team deliverables.

Designed advanced Power BI dashboards with DAX and row-level security to visualize risk indicators such as DPD, charge-offs, and exposure levels; this helped credit controllers monitor changes in borrower behavior in near-real time.

Deployed Kafka-based streaming systems to capture card swipes, ACH transfers, and deposit events in real-time, triggering fraud analytics models that reduced false positives and cut manual investigation latency from 27 minutes to under 9.

Performed borrower segmentation using unsupervised learning techniques (K-Means, hierarchical clustering) in R; categorized users by payment patterns and socio-demographics, which drove tailored loan restructuring and product recommendations.

Created scenario-based stress models using Advanced Excel with VBA automation, simulating policy outcomes under varying macroeconomic conditions; this analysis improved the precision of default forecasting by 19% during regulatory stress testing cycles.

Documented enterprise-wide data workflows, relationship diagrams, and ETL metadata dictionaries using MS Word and Visio, enabling transparent data lineage tracking for audits and reducing interdepartmental reconciliation errors.

Orchestrated UAT planning for fraud and BI modules, preparing traceability matrices, conducting stakeholder walkthroughs, and closing 100% of feedback tickets prior to production deployment.

Delivered board-ready stakeholder presentations and compliance reports using PowerPoint and Excel, ensuring that BI deliverables met regulatory mandates and facilitated successful quarterly business reviews.

EDUCATION

Master of Science in Data Science - University of Houston - Clear Lake (UHCL), Houston, Tx, USA Jan 2023 – Dec 2024

Bachelor of Technology in Metallurgical Engineering - Indian Institute of Technology (IIT) BHU, Varanasi, IN Jul 2017 – May 2021

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