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Responsibilities

The HR Lifecycle Operations team, endeavors to continuously build and deliver a seamless and positive employee experience across the whole employee lifecycle. We are dedicated to leading with care and have empathy in mind. We strive to develop efficient and simple people processes, systems, policies, and programs. We aspire to ensure employees feel heard and that they are given the appropriate resources and support needed to be effective and efficient during their careers. As a Benefits Specialist at TikTok, you will be supporting various employee benefits, including but not limited to Leave of Absence (LOA), healthcare benefits, and 401(k) retirement plan. The ideal candidate should have strong experience and knowledge in leave management, benefits operation and applicable compliance requirements per different types of plans, along with benefits vendor management and system optimization experience.

The leave of Absence Analyst is responsible for auditing, analyzing, and visualizing leave-of-absence data (e.g., sick leave, parental leave, medical leave, unpaid leave) across the organization. By identifying trends, anomalies, and root causes of leave patterns, the role provides data-driven insights to optimize LOA policies, reduce excessive leave risks, improve workforce scheduling efficiency, and enhance employee well-being. This role collaborates closely with HR business partners, payroll teams, and department managers to align data analysis with business goals and ensure compliance with labor laws (e.g., FMLA in the U.S., statutory leave regulations in local markets).

As a project intern, you will have the opportunity to engage in impactful short-term projects that provide you with a glimpse of professional real-world experience. You will gain practical skills through on-the-job learning in a fast-paced work environment and develop a deeper understanding of your career interests.

Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities:
LOA Data Analysis & Trend Identification
- Conduct descriptive, diagnostic, and predictive analysis on LOA data:
- Descriptive: Track key LOA metrics (e.g., total LOA cases per quarter, average leave duration by type, department-wise leave rate, approval/rejection rate).
- Diagnostic: Investigate anomalies (e.g., sudden spikes in medical leave in a specific team, unusually long unpaid leave) and identify root causes (e.g., workplace stress, seasonal illnesses, policy gaps).
- Predictive: Forecast future leave demand (e.g., peak parental leave periods, Q4 sick leave trends) to support workforce planning.
- Analyze LOA impact on business operations (e.g., project delays due to key employee leave) and quantify associated costs (e.g., payroll for paid leave, hiring temporary staff).

Reporting & Visualization
- Develop regular (weekly/monthly/quarterly) LOA reports and dashboards for stakeholders (HR leaders, department managers, executives) using tools like Tableau, Power BI, Excel, or SQL.
- Translate complex data insights into clear, actionable recommendations (e.g., "Parental leave duration in Engineering is 20% longer than company average-suggest updating policy to align with team needs").
- Present analysis results in meetings (e.g., quarterly HR reviews) and tailor communication to non-technical audiences.

Policy Optimization & Compliance Support
- Evaluate the effectiveness of existing LOA policies (e.g., "Is the new mental health leave policy reducing unplanned sick days?") using data metrics and employee feedback.
- Provide data support for policy updates (e.g., adjusting paid leave limits, adding new leave types) to ensure alignment with labor laws (e.g., FMLA, EU Working Time Directive) and industry best practices.
- Collaborate with HRBP teams to communicate policy changes to employees and track adoption rates (e.g., how many employees use the new bereavement leave benefit).

Cross-Functional Collaboration
- Partner with payroll teams to ensure LOA data integrates with payroll processes (e.g., accurate calculation of paid leave wages, deduction for unpaid leave).
- Work with department managers to address team-specific LOA issues (e.g., high leave turnover in Customer Service) and develop targeted solutions (e.g., cross-training staff for backup).
- Liaise with tech teams to enhance HRIS functionality for LOA data tracking (e.g., adding custom fields for leave reason codes, automating leave request workflows).

Qualifications

Minimum Qualifications:
- Currently pursuing an Undergraduate/Masters in Data Science, Statistics, Human Resources Management, Business Analytics, or a related field.
- Proficiency in data querying tools (SQL, HQL) to extract LOA data from HRIS/payroll systems.
- Experience with data visualization tools (Tableau, Power BI, Qlik) and spreadsheet software (Advanced Excel: PivotTables, VLOOKUP, macros).
- Basic knowledge of statistical analysis (e.g., trend analysis, correlation, forecasting) and data cleaning techniques.
- Understanding of leave-of-absence types (sick, parental, medical, unpaid, statutory leave) and relevant labor laws (e.g., FMLA, local statutory leave regulations).
- Knowledge of HR operations (payroll, workforce planning, employee relations) to contextualize LOA data insights.

Preferred Qualifications:
- Experience in HR analytics, workforce analytics, or data analysis (preferably with a focus on leave management, payroll, or employee relations).
- Certification in data analytics (e.g., Google Data Analytics Professional Certificate, Tableau Desktop Specialist) or HR (e.g., SHRM-CP, PHR).
- Experience working in a global organization (familiarity with US leave policies and multi-country data standards).
- Familiarity with HRIS platforms (Workday, ADP) is highly preferred.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

Responsibilities

Qualifications

Qualifications

Minimum Qualifications:
- Currently pursuing an Undergraduate/Masters in Data Science, Statistics, Human Resources Management, Business Analytics, or a related field.
- Proficiency in data querying tools (SQL, HQL) to extract LOA data from HRIS/payroll systems.
- Experience with data visualization tools (Tableau, Power BI, Qlik) and spreadsheet software (Advanced Excel: PivotTables, VLOOKUP, macros).
- Basic knowledge of statistical analysis (e.g., trend analysis, correlation, forecasting) and data cleaning techniques.
- Understanding of leave-of-absence types (sick, parental, medical, unpaid, statutory leave) and relevant labor laws (e.g., FMLA, local statutory leave regulations).
- Knowledge of HR operations (payroll, workforce planning, employee relations) to contextualize LOA data insights.

Preferred Qualifications:
- Experience in HR analytics, workforce analytics, or data analysis (preferably with a focus on leave management, payroll, or employee relations).
- Certification in data analytics (e.g., Google Data Analytics Professional Certificate, Tableau Desktop Specialist) or HR (e.g., SHRM-CP, PHR).
- Experience working in a global organization (familiarity with US leave policies and multi-country data standards).
- Familiarity with HRIS platforms (Workday, ADP) is highly preferred.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

About TikTok

TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

Size: 10,000+ employees
Industry: Technology: Consumer Internet

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