Data Reporting Analyst Resume

OBJECTIVE

College graduate attentive to medical data. Passionate about studying how to improve performance. Seeking to leverage data analytical skills to improve corporate performance as a data analyst.

TECHNICAL SKILLS

Visualization Tools: Tableau Desktop, Plotly, Chart, D3.JS, Python

Analytical/Migration: Tableau, Power - BI

Databases: MySQL, MS-Access

Programming: R Studio, Python, SAS

Version Control: GIT, Github

Data formatting: Advance Excel, JSON, CSV, Office word, PowerPoint

PROFESSIONAL EXPERIENCE

Data Reporting Analyst

Confidential

Responsibilities:

Formulating and testing queries to build billing system reconciliation checks
Knowing tables, schemas, and stored procedures related to assigned business processes
Keep up to date with consistently changing business processes
Finding faulty processes and suggest changes, escalate the need to resolve an issue based on severity.
Multitask projects and work on highest priority tasks and meet deadlines.
Effective organizational, communication, time - management and interpersonal skills; high attention to detail; ability to handle multiple projects/tasks simultaneously while meeting deadlines.
Maintaining ongoing self-study of MS SQL, Access, Excel
Engaging with Sales, Business Analyst, and Operation teams to further investigate raised issues.
Creating SQL reports to further provide visibility to Sales, Operations, and Accounting.
Schedule, assign, and monitor projects of data analysts and support staff to ensure the successful development and implementation of initiatives.
Providing peer review, training, and oversight.
Conduct formal and informal training pertaining to new analytic approaches, data sources, and production system capabilities.
Collaborating and communicating with a team of data analysts.
Running and dropping every day jobs and researching the data.

Data Analyst intern

Confidential

Responsibilities:

Analysis on oral cancer affected data in Mid-west of US
Applied the machine learning K-Means algorithm on the preprocesseddatato predict the customer behavior and stored the result in HDFS
Visualization on the data using Python.
Used pie charts and donut charts for visualization.