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Full Time Data Analyst Jobs in Puerto Rico (NOW HIRING)

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Full Time Data Analyst information

What does a full time data analyst do?

A Full Time Data Analyst is responsible for collecting, processing, and analyzing large sets of data to help organizations make informed decisions. They use statistical tools and techniques to interpret data trends and patterns, create reports and visualizations, and present actionable insights to stakeholders. Data analysts often work with databases, spreadsheets, and specialized software to ensure data accuracy and reliability. Their work supports business strategies, improves efficiency, and identifies opportunities for growth.

What are the key skills and qualifications needed to thrive as a full time data analyst, and why are they important?

To thrive as a Full Time Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Python, Excel, and visualization platforms such as Tableau or Power BI is typically required. Strong problem-solving abilities, communication skills, and attention to detail help analysts present actionable insights and collaborate effectively with stakeholders. These skills and qualifications are crucial for transforming raw data into meaningful information that drives business decisions.

What are typical collaboration partners for a full time data analyst, and how do they work together on projects?

Full Time Data Analysts frequently collaborate with cross-functional teams such as business stakeholders, software engineers, and product managers. They work closely with these partners to understand data needs, define project goals, and translate technical findings into actionable business insights. Regular meetings, data review sessions, and feedback loops are common practices to ensure alignment and effective communication throughout a project's lifecycle. This collaborative approach helps ensure that data-driven recommendations are both relevant and implementable.

What is the difference between Full Time Data Analyst vs Part Time Data Analyst?

AspectFull Time Data AnalystPart Time Data Analyst
Work HoursTypically 35-40 hours per weekLess than 30 hours per week
Employment StatusFull-time employmentPart-time employment
CertificationsOften requires relevant degrees and certificationsMay require similar credentials but with flexible schedules
Work EnvironmentOffice or remote, full-time engagementFlexible, part-time roles often remote or freelance

Full Time Data Analysts work regular hours, often in a dedicated office or remote setting, with full employment benefits. Part Time Data Analysts work fewer hours, offering flexibility but typically with limited benefits. Both roles require similar skills and certifications, but the commitment level differs.

What are the most commonly searched types of Data Analyst jobs in Puerto Rico?

The most popular types of Data Analyst jobs in Puerto Rico are:

What cities in Puerto Rico are hiring for Full Time Data Analyst jobs?

Cities in Puerto Rico with the most Full Time Data Analyst job openings:

Full Time Data Analyst jobs near you

Data Scientist (Statistician) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Ponce, PR • On-site

$125K/yr

Full-time

Posted 6 days ago

Internal Revenue Service rating

7.5

Company rating: 7.5 out of 10

Based on 129 frontline employees who took The Breakroom Quiz

130th of 295 rated public sector bodies

Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:
  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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