Data Analytics Specialist with 5+ Years Experience

Deepak Krishna Kasaraneni Data Analyst

Columbia, SC +1-803-***-**** ************@*****.*** LinkedIn SUMMARY

Data Analyst with 5+ years of experience analyzing large datasets to support business, operational, and financial decisions. Skilled in SQL, Python, Tableau, Power BI, Excel, and cloud data platforms. Proven in automating reporting, improving data quality, and optimizing analytics workflows. Adept at translating business needs into actionable insights and collaborating with cross-functional teams to deliver measurable business impact.

TECHNICAL SKILLS

Data Analysis & Programming: SQL (Complex Joins, CTEs, Window Functions, Subqueries), Python (Pandas, NumPy, Exploratory Data Analysis), Excel (Power Query, Pivot Tables, Advanced Formulas, VBA basics) Business Intelligence & Visualization: Tableau (Calculated Fields, LOD Expressions, Dashboards), Power BI (DAX, Data Modeling, KPI Reporting), Executive and Operational Reporting

Databases & Data Platforms, Snowflake, PostgreSQL, MySQL, Google BigQuery Analytics Techniques: Descriptive and Diagnostic Analytics, Trend and Time-Series Analysis, Forecasting, A/B Testing and Experiment Analysis, Regression Analysis, KPI Definition and Performance Tracking Data Engineering Fundamentals: ETL / ELT Pipelines, Data Validation and Reconciliation, Star Schema and Dimensional Modeling, Data Quality Monitoring

Business Exposure & Collaboration: Operations and Cost Analysis, Customer and Utilization Analytics, Stakeholder Requirement Gathering, Cross-Functional Collaboration, HIPAA Awareness and Data Governance PROFESSIONAL EXPERIENCE

Data Analyst

UnitedHealth Group - South Carolina Feb 2025 - Present

Designed and maintained Tableau and Power BI dashboards using claims, provider, and member data, reducing manual reporting effort by 40% for operations and finance teams.

Optimized complex SQL queries using CTEs and window functions, improving dashboard refresh performance by 30% and improving data accessibility for stakeholders.

Conducted utilization and cost analysis across multiple service lines, identifying cost optimization opportunities totaling ~$2.5M annually, validated by finance leadership.

Automated recurring data preparation and reporting workflows using Snowflake and Excel Power Query, improving data freshness and reducing reporting errors by 25%.

Built short-term time-series forecasting models in Python to estimate admission and utilization trends, supporting capacity planning and resource allocation discussions.

Implemented data validation checks, reconciliation logic, and role-based access controls to ensure compliant and reliable analytics delivery.

Partnered with product owners, operations managers, and clinical stakeholders to define KPIs and translate business requirements into actionable insights.

Data Analyst

CitiusTech - Client-Facing Analytics Projects Jun 2019 - Dec 2022

Developed SQL- and Python-based ETL pipelines to standardize structured datasets, improving data accuracy from ~82% to 97% based on internal data quality audits.

Automated Excel and Power Query reporting workflows, reducing report turnaround time by 75% and improving analyst productivity.

Built Tableau dashboards tracking operational KPIs, utilization metrics, performance trends, and outcome indicators used by leadership teams.

Applied regression and classification techniques to support outcome analysis and business performance evaluation initiatives.

Performed A/B testing analysis for engagement programs, contributing to a 10% improvement in key adoption and adherence metrics.

Collaborated with analysts, data engineers, QA teams, and client stakeholders to gather requirements and deliver analytics aligned with business goals.

Data Analyst

Hexaware Technologies Mar 2018 - May 2019

Automated recurring financial and operational reporting using SQL, Excel, and VBA, improving efficiency and saving 20+ analyst hours per week.

Performed fraud and anomaly detection analysis across MySQL and PostgreSQL datasets, optimizing query logic and reducing false positives by 18%.

Conducted customer segmentation, revenue analysis, and exploratory data analysis (EDA) to identify key business drivers and growth opportunities.

Applied hypothesis testing and statistical analysis to support data-driven decision-making and business strategy.

Implemented data validation, reconciliation, and quality checks to ensure accurate, consistent, and reliable reporting. EDUCATION

Master of Science in Data Analytics Northeastern University - Boston, MA Dec 2024

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