Data Extraction and Transformation: Proficient in extracting, merging, cleansing, and transforming data from various sources to prepare it for analysis.
Critical Thinking and Validation: Apply critical thinking skills to validate logic and outputs, ensuring they align with known sources and understanding of the business.
Data Manipulation: Comfortable with data manipulation languages, particularly SQL and Python, to query and manipulate data efficiently.
Data Trend Identification: Able to identify trends and patterns within datasets, extracting meaningful insights to support decision-making.
Root Cause Analysis: Proactively triage operational alarms, exceptions, and failures, conduct root cause analysis, communicate with relevant parties, contribute to resolution, and implement preventive measures.

Requirements Gathering: Collaborate with business users and stakeholders to understand their reporting needs and translate them into technical requirements, ensuring that the reporting solutions meet their expectations.
Report Development: Develop and maintain reports that effectively communicate key performance indicators
Dashboard Development: Develop and maintain reports that effectively communicate key performance indicators by extract and manipulate data, perform aggregations, and create meaningful data sets using SQL or Python.
Ad-hoc Reporting: Capable of delivering ad-hoc reports to address specific business needs and automate the routine report generation process.

Rae C

A highly versatile data professional with over 4 years of experience empowering operational and engineering teams in the healthcare industry.

Proficient in implementing effective monitoring processes, delivering actionable insights, improving data quality, and creating self-service dashboards to empower stakeholders in making data-driven decisions.

Licenses & Certifications

Resume

Work Experience

Skills & Experience

Education

Recommendations

4+ yr

Earning an 'Exceptional Performance' rating in annual performance reviews from various managers, showcasing exceptional dedication and expertise year after year.

100%

on time delivery

Achieved >60%

time savings through the effective implementation of report automation

"Rae is likely the single most independent individual contributor in the team. She can take an idea, break it into action items, and make measurable progress on those items every single week."

"One of Rae's greatest strengths is her open-mindedness. She is genuinely appreciative of feedback on her own performance, and she has no personal attachment to solutions, which allows her to consider input from others and appropriately apply that perspective/new information."

Performance review feedback provided by the previous manager

"As a Production Data Analyst, Rae has had a broader impact and contribution. Besides the impressive analysis effort, the most impressive accomplishment is her creating a whole new process for parsing Jenkins console outputs that were previously unparseable (and unstorable). She utilized the Jenkins API and created a new process for parsing and storing that data for future use."
"She has made countless enhancements to the data monitoring process including new GitHub workflows, analyzing and breaking out the daily file ingestion process, modifying the threshold of triggered alerts, and putting all of that on the Jenkins pipeline for automation."

Performance review feedback provided by the previous manager

"Rae has also been a pillar of support for the new hires. She has a very calming and supportive presence that a lot of new hires rely on. Consequently, she's helped unblock countless folks and answered a ton of questions from new hires and really helped support the team's sustained growth."

Performance review feedback provided by the previous manager

Requirements Gathering and Analysis: Collaborated with the client implementation and success team to gather data requirements and understand their specific needs and objectives. Analyzed and assessed feasibility of data-related requests, providing effective recommendations for meeting requirements.
Data Integration and Onboarding: Assisted the client implementation and success team in seamlessly integrating and onboarding clients' data into the system or platform.
Support: Highly knowledgeable in data origin, mapping, and utilization, with a deep understanding of how data specifications impact product workflows. Demonstrated proficiency in effectively communicating data requirements to both technical and non-technical stakeholders. Promptly addressed technical inquiries, issues, or requests with accuracy, ensuring timely resolutions.

- Claim Data Management: Proficient in performing data mapping, cleaning, and verification on complex healthcare payer & PBM claims and clinical data, encompassing ICD diagnosis codes, procedure codes, CPT codes, revenue codes, and NDC Rx codes.
- Membership Data Assessment: Experience in calculating baseline and trend metrics to assess the health outcomes and patterns of covered lives.

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Start with the customer – find out what they want and give it to them.

Start with the customer – find out what they want and give it to them.

Start with the customer – find out what they want and give it to them.

Projects

Recent Dashboard Creations

*Note: Specific details on the dashboard have been concealed

The Pipeline Execution Dashboard

The File Processing Dashboard

The Login Activity Dashboard

The Landing Dashboard

*Note: Specific details on the dashboard have been concealed

The Summery Dashboard

*Note: Specific details on the dashboard have been concealed

The Performance Dashboard

ETL Report Automation Example

1Develop a scriptfor making API calls to retrieve data from customer support software.
2. The script cleans and logs refined information into a relational table for report generation and trend analysis for a dashboard.
3. Schedule the script on Jenkins pipeline for daily table back-fill to refresh reports and dashboards regularly.

Integrated Recruit Data Fluctuation Monitoring and Categorization Solution

The Goal

Create a process to effectively monitor and notify cross functional teams (the client implementation team, the operation team and the marketing team) about any changes in the number of recruits, which occurred due to the data feeds processed yesterday.

The Result

Increased Efficiency: By automating the monitoring process with the Jenkins pipeline, the process runs daily without manual intervention. This results in significant time savings for the teams involved.
> 50% of investigation time saved: Categorizing cases into different investigation buckets enables teams to prioritize and focus their efforts efficiently
Achieved 100% comprehensive case logging for future auditing requirements and maximizing analysis opportunities.
Standardized Process

Tool & Platform

Platform: Redshift, Jenkins, Metabase, GitHub, Salesforce
Language: SQL, batch script

The High Level Steps to Complete the Project

Conducted the exploratory analysis and observed different scenarios
Designed the SQL logic (the logic is shown above in the flowchart) to efficiently capture and log accounts that experience fluctuation in recruit counts and categorize cases into different investigation buckets.
Put the script on the Jenkins pipeline and schedule it to run everyday
Created a user-friendly Metabase dashboard that can effectively cater to various look back requirements to view previous concerning cases
Set up an automatic email notification to inform the cross functional teams about the daily concerning cases
Develop comprehensive documentation and training materials that outline the step-by-step process, as well as troubleshooting techniques, for handling cases that trigger the alarm.

Automated Detection of Client Data Onboarding Delays

The Goal

Establish an efficient process for monitoring the status of client's incoming data, promptly identifying the causes of delays on the pipeline and automate the Jira ticket creation process to track all issues.

Tool & Platform

Platform: Redshift, Jenkins, S3, GitHub, Jira
Language: SQL, Python, batch script

The High-Level Steps to Complete the Project

Use SQL & Python to implement the below logic to identify & categized the delay:

Compile a list of active files, their corresponding submission cadence and internal file dropped location path.
Create a rule to identify delays and sync with the manger for approval.
Categorize the delay reason:
- use the MFT file log to identify whether the delay is due to file submission delay by the data provider
- or it's related to the internal file location configuration issue.
Log all the alerts in an internal table for the Jira API to print out internal investigation tickets.

2. Put the script on the Jenkins pipeline and schedule it to run every day to print out tickets.

3. Developed comprehensive documentation and training materials that outline the step-by-step process as well as troubleshooting techniques, for handling cases that trigger the alarm.

Enhanced Client's Data Onboarding Workflow with Automated Issue Tracking

The Goal

Establish a process to effectively monitor and detect failures during the pipeline for onboarding clients' external data feeds for the member enrollment process, log these failures, and automate the Jira ticket creation process to track all issues.

Tool & Platform

Platform: Redshift, Jenkins, S3, GitHub, Jira
Language: SQL, Python, batch script

The High-Level Steps to Complete the Project

Collaborate closely with the data engineering team to design a dependable data model and ingestion tool, aimed at storing configured file information and efficiently consuming data. Play an active role in the development process by sharing operational perspectives to drive improvement.
After the new tool and data model is released, create a script to automatically identify new ingestion failure every week for the ticket creation.
Put the script on the Jenkins pipeline and schedule it to run every week.
Create a comprehensive training for the operation team that covers the file ingestion production behavior and the data flow process. Outline a step-by-step troubleshooting process for handling ingestion failure tickets.

Prevalence Analysis

Releasing soon

Data Extraction and Transformation: Proficient in extracting, merging, cleansing, and transforming data from various sources to prepare it for analysis.

Rae C

Social Media

Resume

Recommendations

Earning an 'Exceptional Performance' rating in annual performance reviews from various managers, showcasing exceptional dedication and expertise year after year.

on time delivery

Projects