Data Analyst Business Intelligence

Keerthi Marabathula

Data Analyst

Location: Missouri, USA Email:************@*****.*** Contact No: 423-***-****

Professional Summary:

•Results-driven Data Analyst experience in the healthcare and financial sectors.

•Skilled in integrating real-time fraud detection algorithms into operational systems via AWS Lambda, enhancing organizational security through effective alert systems.

•Proficient in extracting insights from large datasets using SQL, Teradata, Hadoop/HIVE/Sqoop and Apache Spark, enabling data- driven decision-making across diverse business contexts.

•Strong understanding of Agile/Scrum methodologies, adept at translating complex business requirements into technical solutions, and optimizing the performance of TensorFlow models.

•Committed to adding value to teams through innovative data solutions while proactively addressing potential disruptions in data integrity and accessibility.

•Led compliance initiatives for loan reviews, ensuring alignment with lender requirements while managing data deliverables and high-level data modelling.

•Streamlined data cleansing processes and reporting through advanced Excel techniques and SQL, producing complex reports to audit healthcare assets effectively.

•Leveraged Business Intelligence tools like Power BI to create dynamic dashboards and ad hoc reports, facilitating data- driven solutions to business challenges.

•Experienced in data pre-processing and statistical analysis with Python, utilizing libraries such as Pandas and NumPy, and conducting A/B testing to refine marketing strategies and improve user engagement.

•Expertise in developing and maintaining comprehensive data dictionaries and definitions utilizing Collibra, alongside proficiency in statistical analysis and data visualization through Python and R, ensuring clarity and accessibility of data.

•Proven ability to design and refine healthcare data models using SQL, significantly enhancing analytical capabilities and improving forecasting accuracy in healthcare settings.

•Extensive knowledge of HIPAA compliance and various medical plans, including HMO, PPO, POS, EPO, and Medicare/Medicaid, ensuring adherence to regulatory standards in data handling.

•Enhanced organizational decision-making processes by automating data access and reporting, leading to increased operational efficiency and faster business development cycles.

•Developed predictive models that effectively addressed customer retention challenges, contributing to revenue growth through improved customer engagement strategies.

Technical Skills:

Methodologies:

SDLC, Agile (Scrum), Waterfall.

Programming Languages:

Python, SQL, R.

Packages:

Scikit-Learn, ggplot2, Pandas, NumPy, Matplotlib, SciPy, Seaborn.

Visualization Tools:

Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP, VBA, Macros)

IDEs:

Visual Studio Code, PyCharm, Jupyter Notebook.

Database Management:

MySQL, MongoDB, PostgreSQL, Oracle.

Cloud Platforms:

Amazon Web Services (AWS).

Other Technologies:

SSIS, SSRS, SAS, Machine Learning Algorithms, ETL, Probability distributions, Confidence Intervals, ANOVA, Hypothesis Testing, Regression Analysis, Linear Algebra, Advance

Analytics, Data Mining, Data Visualization, Data warehousing, Data transformation, Data Storytelling, Association rules, Clustering, Classification, Regression, A/B Testing, Forecasting & Modelling, Data Cleaning, Data Wrangling, MS Office Suite, Alteryx, Jira.

Soft Skills:

Time management, Leadership, Management, Problem-solving, Negotiation, Decision- Making, Documentation and Presentation, Verbal communication.

Version Control:

Git, GitHub, SVN.

Operating Systems:

Windows, Linux, Mac iOS.

Professional Experience:

Cigna Healthcare – CT (Remote) Aug 20– Current

Data Analyst

•Led a project to streamline the HEDIS reporting process by automating the data extraction from Epic's Clarity database, reducing reporting time by 30%.

•Created and maintained Data dictionaries, data mapping, and data definition using Collibra as a data governance tool and performing statistical data analysis and visualization using Python and R.

•Led the development of a claims analytics system to identify and reduce fraud, successfully decreasing fraudulent claims by 15%. Integrated data from claims databases and financial records using SQL for data extraction.

•Assist with performing various analyses relating to Medicaid engagements, including the analysis of medical claims data to identify fraud, waste or abuse of Medicaid or other health care system funds.

•Utilized SQL for data extraction from healthcare databases containing patient records, demographics, and medical history.

•Leveraged Alteryx to integrate various data sources, including databases, cloud services, and flat files, enabling comprehensive data analysis.

•Utilized SAS to perform statistical analysis on patient outcomes, identifying key factors that led to a 7% reduction in readmission rates.

•Integrated Electronic Health Record (EHR) data into analytical workflows to ensure a comprehensive view of patient health and medical history.

•Utilized Alteryx to blend data from disparate sources, enhancing the scope and accuracy of analysis without the need for complex coding.

•Supports internal population based medical management data efforts by performing the clinical and cost based analysis of medical and EPIC data using SAS. Population data include Medicare and Medicaid.

•Designed and implemented ETL processes to streamline data flow between different systems, reducing data processing time by 30% and ensuring high data accuracy.

•Developed and optimized healthcare insurance models using SQL to enhance data analysis capabilities, improving healthcare insurance forecasting accuracy by 18%.

•Integrated real-time fraud detection algorithms into operational systems, leveraging AWS Lambda functions to trigger alerts & notifications for suspicious activities, reducing fraudulent losses by 25%.

•Conducted exploratory data analysis (EDA) to identify trends, patterns, and correlations in population health data, using Python libraries such as Pandas and NumPy.

•Experience with Medicare or Medicaid reimbursement, including cost reports, Medicare DSH and/or Medicare bad debts, is a significant advantage.

•Developed a suite of automated reports in Tableau for clinical teams, enhancing real-time tracking of HEDIS measures and improving patient care strategies.

•Worked on integrating data from Epic Systems with external data sources to improve the accuracy of reports and patient data insights.

•Applied advanced Excel functions, such as VLOOKUP and PivotTables, for comprehensive data analysis, resulting in a 25% improvement in reporting accuracy.

•Developed predictive models using scikit-learn in Python to forecast healthcare resource utilization, including hospital admissions, emergency room visits, and specialist consultations.

•Understanding business requirements and providing workable technical solutions through Agile/Scrum steps after testing, user acceptance, and optimized TensorFlow models for efficiency.

•Utilized Excel and Access to launch theoretical claim queries into the system.

•Implemented a dashboard system using Power BI to track and report on healthcare quality metrics, including patient satisfaction scores, readmission rates, and adherence to clinical guidelines.

•Utilized process mining tools to visualize and quantify workflow inefficiencies in healthcare processes, such as patient admission, discharge, and follow-up care.

•Ensured compliance with data privacy laws (HIPAA) by implementing robust data security practices, maintaining 100% compliance during internal audits.

•Prototyped new and complex reporting using knowledge of healthcare administrative claims data and advanced SQL coding skills.

•Enhanced decision-making processes, resulting in a 10% increase in the speed of business development.

•Improved operational efficiency by 18% through automation and enhanced data accessibility.

•Developed and implemented predictive models that reduced churn rates by 15% and increased revenue by $ 5 million annually.

•Understanding business requirements and providing workable technical solutions through Agile/Scrum steps after testing, user acceptance, and optimized TensorFlow models for efficiency

IBM– India Aug 2021 – Nov2022

Data Analyst

•Regularly executed data cleaning, transformation and pre-processing techniques to maintain data integrity, ensuring accuracy and reliability for all analytical outputs.

•Improved data cleansing processes by 25% through the development of custom Python scripts, reducing data preparation time and enhancing the accuracy of predictive models.

•Worked on various data mapping initiatives, ensuring seamless integration of data from source systems into Teradata, enhancing data accessibility and usability for analysis.

•Streamlined reporting processes by leveraging advanced Excel and SQL queries, optimizing the organization and visualization of large datasets, improving data accuracy by 18% and enhancing decision-making efficiency.

•Managed and delivered 100% of data management projects, including business need analysis and high-level data modelling, resulting in improved data accuracy and alignment with business objectives.

•Developed interactive Power BI dashboards and ad hoc reports to solve complex business problems, driving a 22% increase in process efficiency and aiding in strategic decision-making across departments.

•Implemented a cloud-based data storage and processing solution using Amazon Web Services (AWS), including Amazon S3 for data storage, Amazon Athena for querying, and AWS Glue for ETL processes, resulting in a 50% reduction in infrastructure costs and improved scalability.

•Engaged in extensive data management activities, conducting thorough data analysis and gap assessments to identify areas for improvement and optimize data utilization.

•Analysed, documented and presented user survey results, leading to an 18% enhancement in customer communication strategies, thereby improving user engagement and satisfaction metrics.

•Automated visual workflows in Alteryx to streamline data transformation processes, reducing data processing time by 40% and improving consistency across 25+ datasets.

•Built and managed complex SQL reports to audit over $1M in debt, tracking financial performance across 500+ borrowers and lenders, ensuring 100% compliance and accurate financial reporting.

•Architected a robust data warehouse utilizing SQL Server and Excel to efficiently store, organize and analyse over 50GB of data, ensuring high performance and scalability for future data needs.

•Utilized Python and libraries like Matplotlib to execute advanced data extraction, cleaning, and visualization techniques, transforming complex datasets into clear, actionable insights for stakeholders.

•Utilized Alteryx for advanced data pre-processing by managing complex joins, calculations and transformations, ensuring 98% data accuracy for visualization in Tableau and Power BI, improving report generation efficiency by 30%.

•Constructed sophisticated data models that extract actionable insights from customer data, resulting in a 14% increase in successful sales initiatives and informed business strategies.

•Utilized Tableau to develop interactive dashboards and comprehensive reports that track business performance metrics (KPIs), enabling stakeholders to make data-driven decisions.

Education:

Master of Business Analytics and Project Management – Southeast Missouri state university, Cape Girardeau, MO, USA Bachelor of Technology - Jawaharlal Nehru Technological University Kakinada, Guntur, AP, INDIA

Certification

1.Certified Accomplishment of Youth Employment Program by TCS September 2021

2.Certified in Microsoft Technologies on introduction of programming using python by MADBLOCKs Private Limited

--MAY 2021

3. Certified of women empowerment program by DXC Technologies December 2021

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