Data Analyst

Found in: Talent US C2 - 2 weeks ago

Irvine, United States Hubstaff Full time

We are seeking a Mid-Level Data Analyst to join our financial company's team. The Data Analyst will be responsible for designing and implementing complex analysis projects, analyzing large datasets, and delivering actionable insights to drive strategic business decisions.

Benefits:

Competitive salary Strong support system Salary increase starting on your first year of employment (based on performance) Monthly Performance Incentive (only for full-time roles | based on given metrics |can range from $40 - $50) Health benefit ($30/month) No computer activity monitoring Training materials for upskilling provided Paid holiday leaves (depending on the holidays that the client observes) Paid sick leaves (sick leave convertible to cash if perfect attendance) Paid planned leaves Allowance for SSS and Pag-ibig contribution ($20/month)

Key Responsibilities:

Design and implement complex analysis projects to address specific business problems, collaborating with various teams to understand project objectives. Develop, implement, and maintain databases and data systems essential for project and departmental functions. Analyze large datasets to identify trends, patterns, and insights, translating them into actionable business strategies. Lead the development of data-driven reports for senior management and stakeholders. Ensure the integrity and accuracy of data processing and analysis, implementing quality control measures. Mentor entry-level data analysts, providing guidance and support in their projects and professional development. Continuously improve data analysis techniques, tools, and protocols to enhance the quality and efficiency of insights. Ad hoc tasks from the client.

Requirements & Qualifications:

Bachelor's degree in Data Science, Statistics, Computer Science, or a related field. A Masters degree is a plus. 3-5 years of experience in data analysis or a related field. Advanced proficiency in statistical software (e.g., R, Python) and expertise in SQL. Strong experience with data visualization tools (e.g., Tableau, Power BI) and techniques. Solid understanding of machine learning algorithms and statistical modeling techniques. Proven track record of analyzing large datasets and delivering actionable insights. Excellent problem-solving abilities and attention to detail. Strong communication and presentation skills, with the ability to translate complex findings into an understandable format. Undergo 3 days of paid training. If there's an urgency for the role, then the new hire must render an hour of paid OT before or after the shift for 3 weeks. Amenable to work Monday through Friday between 8 AM - 5 PM US Pacific Time Zone(PST).

Preferred Qualifications:

Experience in the financial industry or related sectors. Advanced degree in Data Science, Statistics, or a related field. Certification in relevant areas such as data analysis, machine learning, or statistical modeling. Experience mentoring or leading junior team members in data analysis projects. Knowledge of advanced data analysis techniques, such as predictive analytics and data mining.

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