Senior I, Analytics Engineer

UPMC•Pittsburgh, PA

14h

About The Position

The Senior I, Analytics Engineer reports to the Lead, Analytics Engineer under the direction of the Director, Data Intelligence & Investigations. The Senior I’s primary responsibility is to perform high quality and moderately complex data analytics and visualization projects in support of Internal Audit and Compliance engagements, in a timely manner and in accordance with professional standards. The Senior I contributes to analytics projects by preparing and validating datasets, developing basic-to-moderate analyses and visualizations, and assisting with ongoing monitoring activities. The role supports the development and maintenance of departmental dashboards and scripts. The role supports the development and maintenance of departmental data analytics, risk assessment dashboards, internal KPIs, and automation scripts that support continuous monitoring, investigation, and planning activities. The Senior I is building proficiency in validating the accuracy of their own work products and is accountable for producing workpapers and deliverables (such as analyses and data visualizations) that are professionally written and that reflect an understanding of project objectives and control requirements. The position is actively building proficiency in organizational data repositories to facilitate data analytics work. The Senior I contributes to team knowledge sharing and skills-development while working under regular supervision. The Senior I is beginning to develop an internal network of contacts to facilitate collaboration with other data-oriented teams in external departments and build their knowledge. This position may occasionally lead discrete workstreams within larger projects and primarily participates in meetings with internal stakeholders with direct oversight.

Requirements

Bachelor's degree and 4 years related work experience (or 2 years and preferred certification or master’s degree)
2 years of experience in the areas of Data/Business Analytics, Data Science, Software Development, Data Warehousing, Business Intelligence, Information Technology / Information Security / Auditing.

Nice To Haves

Certification or master’s is preferred.
Data Science, Business Analytics, Health Information Technology, Information Technology/Systems, Information Security, Computer Forensics, Computer Science.
Python, SQL, ACL, PowerBI, Tableau, Snowflake, Epic, and/or other data tools and languages.
Data Analytics, Data Visualization, Programming/Software Engineering, Statistics, Machine Learning, Business Intelligence, Auditing, Information Technology, Health Care, Database/Data Warehouse Management.
CISA, CISSP, CFE, CIA, ACDA, SAS Certified, DASCA Certified, or other data analytics certification, CPA, CHC, CCEP, Six Sigma.
Certification is preferred.
CISA, CISSP, CFE, CIA, ACDA, SAS Certified, DASCA Certified, or other data analytics certification, CPA, CHC, CCEP, Six Sigma.

Responsibilities

Successfully manages several competing demands and is able to manage tasks on time and within budgeted hours.
Enhance the culture through the execution of analytics in support of Internal Audits, Compliance Projects, and Fraud Team investigations.
Increase departmental capabilities for full population testing (and reduce reliance on sampling) in audit work to enhance insight into the severity and frequency of identified audit exceptions.
Meets departmental goals for productivity and is proactive in searching out additional tasks and projects during downtimes.
Possesses solid public speaking and presentation skills, occasionally leading meetings with internal stakeholders.
Is developing executive presence, and an understanding of how to tailor messaging appropriately to different audiences.
Communicates in a professional, structured manner appropriate to the audience, demonstrates awareness of organizational hierarchy, provides timely updates on task status and completion, and incorporates feedback into work products.
Contributes to maintaining the reputation of the team within the department by conducting self-review of code, visualizations, and conclusions for completeness and accuracy before sharing for review by senior staff.
Translates business, fraud-detection, and audit objectives into structured analytical requirements and testable methodologies with minimal guidance from senior staff.
Monitors project work for timeliness and adherence to departmental quality standards and validates evidence is organized to fully support conclusions and findings.
Identifies root cause of issues and proposes valuable and effective solutions, with knowledge of the UPMC organization.
Reviews all workpapers as appropriate and prepares deliverable drafts for review by Discipline or Department Management, ensuring professional writing and value-added industry perspective.
Remains informed of emerging technologies in data analysis and updates in the organization’s IT systems.
Collaborates with project teams to enhance risk assessment, audit planning, root cause identification, and targeted monitoring activities.
Applies working knowledge of risk and control concepts to design and lead valuable analyses for Audit, Compliance, and Fraud Team projects, ensuring accuracy and repeatability.
Actively cultivates a growing understanding of IT, data analysis, and healthcare terminology as well as industry-specific risks relevant to Audit and Compliance.
Periodically attends relevant industry or professional trainings to stay current on industry developments, using this knowledge to inform best practices and data analytics standards within the team.
Demonstrates strong knowledge of data validation, data analysis and visualization techniques, software development methods, data querying and manipulation technologies, and/or relevant business intelligence tools.
Is developing proficiency in at least two programming languages or business intelligence tools (e.g., SQL, Python, ACL) necessary for data analysis in organizational contexts.
Shows a basic understanding of core software development techniques, enabling adaptation to new tools or technical solutions.
Maintains version control and change tracking for analytics scripts, models, and reporting assets in accordance with departmental standards.
Creates code and visualizations in alignment with departmental standards and industry best practices.
Readily approaches common business/analytics problems and participates in the development of appropriate solutions.
Stays current with new and emerging technologies in data analysis and changes in the Organization’s IT systems.
Is developing and demonstrating competency in extracting and combining data from a variety of data warehouses, reporting tools, and systems in use at UPMC.
Is building skills and knowledge towards becoming an analytics subject matter expert in at least two primary UPMC applications, data warehouses, or functional domains (e.g., billing, clinical, fraud, HR, finance, insurance, IT systems).
Is responsible for building, maintaining, and improving departmental scripts, automated tasks, and risk monitoring metrics under the direction of senior staff members.
Proposes design ideas for data analytics and fraud detection tools, occasionally collaborating with similar roles across the organization to support knowledge sharing.
Consistently documents data sources, transformations, assumptions, and methodologies to ensure reproducibility and compliance with departmental standards, templates, and guidelines.
Collaborates with the Director to occasionally recommend enhancements/updates to departmental standards.
Conducts continuous auditing tests and analyzes routine data sets to identify potential issues such as fraud, conveying findings to management.
Performs quality assurance procedures, including validation of logic, results, and supporting evidence to ensure integrity in analytic results and visualizations.
Develops and scripts analytics according to departmental standards for repeatability and peer review, mentoring junior staff in coding best practices.
Proposes testing steps for basic statistical analyses, ensuring adherence to departmental standards and effectiveness.
Monitors project timelines and quality, escalating any concerns to senior staff as identified.
Employs approved LLM tools to support analytics and documentation, ensuring appropriate use, validation of outputs, and compliance with data governance standards.