Temco Logistics is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate based on race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Data Analyst
Location
United States
Posted
47 days ago
Salary
$80K - $85K / year
Seniority
Mid Level
No structured requirement data.
Job Description
Data Analyst
Temco Logistics
Job DetailsJob Location: Pomona Corporate Temco - Pomona, CA 91766Position Type: Full TimeEducation Level: CASalary Range: $80,000.00 - $85,000.00 Salary/yearTravel Percentage: RemoteThe Human Resources Data Analyst will be responsible for analyzing and interpreting data related to employee retention, turnover, investigations, and other HR metrics. This role will help the HR department make data-driven decisions by providing insights into workforce trends, identifying potential issues, and offering recommendations for improving employee engagement and retention. The Data Analyst will work closely with HR leadership to develop reports and dashboards that support strategic decision making. Key Responsibilities: Data Analysis: Analyze HR data related to employee retention, turnover, investigations, performance management, and other HR metrics to identify trends and insights. Data Presentation: Present complex data in a clear and meaningful way through visuals and narrative, enabling non-technical stakeholders to understand key insights. Create practical step-by-step guides that support leaders in adopting and using new dashboards. Reporting: Create regular and ad-hoc reports and dashboards for HR leadership, summarizing key findings, trends, and recommendations for improving workforce outcomes. Data Collection: Work with HR systems (such as HRIS, payroll, and performance management tools) to collect, clean, and validate data for analysis. Metrics Tracking: Track and report on key performance indicators (KPIs) such as employee engagement, retention rates, turnover trends, absenteeism, and time-to-hire. Predictive Analytics: Use predictive models to forecast potential turnover, identify factors contributing to employee disengagement, and suggest proactive strategies to address these issues. Investigations Data: Analyze data related to employee relations investigations, including the frequency and outcomes of complaints, to identify patterns or areas of concern. Retention Strategies: Collaborate with HR to develop data-driven strategies for improving employee retention and engagement based on analyzed data. Stakeholder Collaboration: Work closely with HR leadership, operations, and other departments to ensure data insights are aligned with business goals and strategies. Compliance & Confidentiality: Ensure that data analysis adheres to legal and regulatory requirements, maintaining the confidentiality and security of sensitive HR data. Process Improvement: Identify areas where data collection and analysis processes can be improved and implement solutions to streamline data management. Qualifications: Bachelor’s degree in data science, Statistics, Business Analytics, Human Resources, or a related field. 2-3 years of experience in data analysis, preferably within HR or a related field. Strong proficiency in data analysis tools and software such as Excel, SQL, Tableau, Power BI, DOMO, and/or similar. Familiarity with HR systems and databases (e.g., HRIS, payroll systems, performance management tools). Excellent analytical and problem-solving skills, with the ability to interpret complex data sets. Strong communication skills, with the ability to present data insights to non-technical audiences. Knowledge of HR practices and metrics related to retention, turnover, employee engagement, and investigations. High attention to detail and ability to work with confidential information. Experience with statistical analysis and predictive modeling is a plus. Qualifications
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