Data Analyst Healthcare

Abdullah Shareef

DATA ANALYST

Macon, GA Mobile: 202-***-**** Email: ******************@*****.*** SUMMARY

• Seasoned data analyst with 3+ years of experience in analysing and interpreting large volumes of healthcare data, including electronic health records (EHRs) and claims data, using statistical software to identify trends, patterns, and correlations.

• Proficient in utilizing a wide range of programming languages, including Python, R, SQL, and statistical packages such as NumPy, Pandas, Matplotlib, and SciPy.

• Demonstrated expertise in data visualization using Tableau, Power BI, and Advanced Excel, presenting complex findings in interactive and informative dashboards.

• Strong analytical skills, adept at extracting and querying data from various databases, including MySQL, PostgreSQL, MongoDB, SQL Server, and Oracle.

• Proven track record in applying machine learning algorithms for predictive analytics, resulting in optimized inventory levels and reduction in inventory carrying costs.

• Ensured compliance with healthcare regulations and incorporated best practices in healthcare data analysis.

• Applied domain knowledge of healthcare operations, clinical workflows, and medical terminologies (ICD-10, CPT) to accurately interpret and analyse healthcare data.

• Skilled in customer segmentation projects, employing clustering algorithms like K-Means and hierarchical clustering to drive targeted marketing strategies and achieved increase in customer retention.

• Strong problem-solving and critical thinking abilities, consistently delivering data-driven solutions to meet business objectives and improve decision-making processes.

• Excellent communication and presentation skills, effectively collaborating with cross-functional teams and stakeholders to translate data insights into actionable recommendations. SKILLS

Methodologies: SDLC, Agile, Waterfall

Programming Language: R, Python, SQL

Packages: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn Visualization Tools: Tableau, Power BI, Excel

IDEs: Visual Studio Code, PyCharm, Jupyter Notebook, IntelliJ Database: MySQL, PostgreSQL, MySQL, MongoDB, SQL Server, Oracle Other Technical Skills: SISS, SSRS, Machine Learning Algorithms, CI/CD, ServiceNow, 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, Critical Thinking, Communication Skills, Presentation Skills, Problem-Solving Healthcare: HIPAA, Affordable Care Act and Health Insurance, Electronic Health Record (EHR) Systems.

Version Control Tools: Git, GitHub

Operating Systems: Windows, Linux

EDUCATION

University of North Texas, Denton, Texas

Master of Science in Information Science

Jawaharlal Nehru Technological University, Telangana, India Bachelor in Doctor of Pharmacy

EXPERIENCE

Data Analyst Cigna Healthcare, Remote July 2022-Present

• Leverage data analytics and anomaly detection (Isolation Forest, One-Class SVM) to optimize health insurance claims process, aiming to reduce fraud and improve claim approval accuracy at Cigna Healthcare.

• Utilize SQL and Python for data extraction, pre-processing, and exploratory analysis of diverse claims data sources.

• Implement Isolation Forest and One-Class SVM algorithms to identify and flag potentially fraudulent claims, achieving 90% detection accuracy and reducing false positives by 25%.

• Collaborate with domain experts and investigators to develop a quantified fraud risk score for prioritizing investigations and allocating resources efficiently.

• Utilize Tableau to create interactive dashboards and visualizations, showcasing claim distribution, anomalies, and fraud detection performance over time.

• Experience a significant 15% reduction in fraudulent claims, leading to substantial cost savings for Cigna Healthcare.

• Enhance the claims approval process by proactively addressing potential fraud instances, streamlining operations, and expediting legitimate claim approvals.

• Ensure fair treatment for genuine claims, preventing delays and boosting customer satisfaction by promptly processing valid claims.

Data Analyst Apollo Hospitals, India June 2019-Aug 2021

● Utilize data analytics and predictive modelling (Python) to optimize hospital staff scheduling and resource allocation, aiming for efficient patient care and cost savings.

● Analyse historical staffing data, patient admission rates, and departmental workloads to identify patterns and trends.

● Develop forecasting models to predict patient demand and specialty requirements for accurate staff planning.

● Implement an algorithm to allocate staff shifts based on expertise and availability, ensuring optimal coverage.

● Achieve a 15% reduction in overtime expenses by efficiently scheduling staff without compromising care quality.

● Improve staff utilization by 20% through data-driven scheduling, maximizing productivity.

● Utilize Tableau to create interactive dashboards for real-time insights on staff allocation and performance metrics.

● Ensure timely and appropriate care by having the right staff in place to meet patient demands.

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