Strategic Programs Senior Analyst

About The Role

Role

Payroll Data Scientist

Accenture Hiring Level

Level 10

About The Role

As a Data Scientist in the Payroll domain, you will leverage data to optimize payroll operations, ensure compliance, detect anomalies, and support strategic decision-making. You will work closely with HR, Finance, and IT teams to build predictive models, automate reporting, and enhance payroll accuracy and efficiency.

• Data Analysis and Interpretation:
• Utilizing advanced analytical techniques to analyze payroll data, identify trends, anomalies, and opportunities for improvement.
• Use statistical methods and tools to find patterns, trends, and relationships.
• Develop predictive models for payroll forecasting, headcount planning, and cost optimization.
• Reporting and Dashboard Development:
• Designing and maintaining comprehensive dashboards and reports that provide actionable insights to stakeholders.
• Build automations to gather data from various sources like databases, APIs, web scraping, or sensors.
• Process Optimization:
• Collaborate with payroll operations teams to streamline processes and enhance efficiency based on data-driven recommendations.
• Translate complex data results into actionable business strategies.
• Integrate Enterprise Systems
• Connect AI solutions to internal systems via APIs
• Design and implement REST API integrations (authentication, data exchange)
• Work with structured and unstructured data across multiple sources
• Process Support:
• Execute the process accurately and timely as hands on processor.
• Escalate issues and seek advice when faced with complex issues/problems.
• Creates a logical plan, realistic estimates and schedule for an activity or project segment.
• Ensure Local Work Instructions are followed and updated regularly and train the team members on process updates.
• Ensure process controls are in place; Maintain, validate and update process documentations.
• Perform Root Cause Analysison issues faces and suggest appropriate corrective action for current remediation and future control.
• Participates in Knowledge Transfer of any process and acquires in depth knowledge of process as an SME.
• Strengthen work relationship with Onshore Teams and other internal teams.
• Participate in conference calls and prepare ˜minutes of meeting'.

Qualification

Background Requirements

Criteria

Minimum Requirement

Evaluation Methodology

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Business Analytics, or a related field

To be verified through documents submitted at the time of interview

Total Years of Experience

4 - 6 years of Experience

To be verified through documents submitted at the time of interview

Total Years of Role Specific Experience

3 - 4 years of Payroll Analytics Experience

To be verified through documents submitted at the time of interview

Skills Knowledge Required

Skills / Knowledge

Mandatory Vs Preferred

Measure of Skill Proficiency

Evaluation Methodology

Programming (Python, R, SQL)

Mandatory

Met Expectation /Not Met Expectation

Practice

Hands-on experience with APIs

i. REST APIs, authentication (OAuth, tokens)

ii.System integration experience

Mandatory

Met Expectation /Not Met Expectation

Practice

Payroll Knowledge

Preferred

Met Expectation /Not Met Expectation

Interview

Statistics Math (Probability, regression, hypothesis testing)

Mandatory

Met Expectation /Not Met Expectation

Practice

Payroll Systems (Example:Workday / Dayforce / SAP) and CRM/Workflow tools (SNOW / WQM / CRM etc.)

Preferred

Met Expectation /Not Met Expectation

Interview

MS Office

Preferred

Met Expectation /Not Met Expectation

Practice

Machine Learning (Classification, clustering, recommendation systems)

Mandatory

Met Expectation /Not Met Expectation

Practice

Communication Skills

Mandatory

Met Expectation /Not Met Expectation

Interview

Data Modelling / Analytics (Example:PowerBI / Tableau / MS Access)

Mandatory

Met Expectation /Not Met Expectation

Practice

Microsoft PowerApps

Mandatory

Met Expectation /Not Met Expectation

Practice

Power Query

Mandatory

Met Expectation /Not Met Expectation

Practice

Problem solving skills (Analytical skills / Collaborative thinking/ Adaptable to change)

Mandatory

Met Expectation /Not Met Expectation

Interview

Note for Sourcing

Candidate meets the educational, industry role specific experience criteria to be put across HR screening.

Note for HR Screening

Candidate meets the sourcing criteria within the standard compensation bracket for the role, basic communication skills to be put through for written assessment

Note for Ops Interview

Candidate nearer to the target on skill/knowledge required should be put on hold and considered again depending on the pipeline of the resources available to meet the hiring targets

Note for Offer Management

Candidates fit the role requirement but above the standard compensation offered should be referred to delivery/transition lead for decision