2

Entry Level Open Source Intelligence Analyst Jobs in Indiana

FEDITC, LLC is a fast-growing business supporting DoD and other intelligence agencies worldwide ... Learn CSSP toolsets and procedures under mentorship Experience/Skills: * Entry-level position - no ...

FEDITC, LLC is a fast-growing business supporting DoD and other intelligence agencies worldwide ... Learn CSSP toolsets and procedures under mentorship Experience/Skills: * Entry-level position - no ...

Intellectual curiosity * Problem solving and analytical thinking * Ability to develop strong relationships Primary Responsibilities for Entry Level Sales: * Will work directly with our sales team ...

Financial Analyst

Fort Wayne, IN · On-site

$30.92 - $36.18/hr

... Entry Level Job Type & Location This is a Contract to Hire position based out of Fort Wayne, IN ... Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of ...

This role is an entry-level position and is expected to perform assigned duties under established ... Ability to learn and work with business intelligence and reporting tools such as Power BI and ...

... source qualified talent for their open roles. The following position is available to Veterans ... The Financial Analyst is responsible for providing value added reporting and analysis to achieve ...

next page

Showing results 1-20

Entry Level Open Source Intelligence Analyst information

What are the key skills and qualifications needed to thrive as an Entry Level Open Source Intelligence Analyst, and why are they important?

To thrive as an Entry Level Open Source Intelligence Analyst, you need strong research abilities, analytical thinking, and a relevant degree in fields like criminal justice, international relations, or cybersecurity. Familiarity with open-source intelligence (OSINT) tools, data visualization platforms, and basic knowledge of information security protocols are typical technical requirements. Attention to detail, critical thinking, and effective written communication make candidates stand out in this position. These skills and qualities are crucial for accurately gathering, interpreting, and presenting information to support informed decision-making in security or investigative contexts.

What does an Entry Level Open Source Intelligence Analyst do?

An Entry Level Open Source Intelligence (OSINT) Analyst collects, analyzes, and interprets publicly available information to help organizations make informed decisions. This role involves researching data from sources like news articles, social media, public records, and websites to identify trends, threats, or relevant insights. Analysts often support security, law enforcement, or business operations by preparing reports and briefings based on their findings. Entry-level analysts typically use specialized tools and follow strict ethical guidelines to ensure their work is accurate and legal.

What are some common challenges faced by entry-level Open Source Intelligence Analysts, and how can they be addressed?

Entry-level Open Source Intelligence (OSINT) Analysts often face challenges such as information overload, verifying the credibility of sources, and adapting to rapidly changing data landscapes. To address these, developing strong research methodologies, learning to use advanced OSINT tools, and collaborating with more experienced team members are essential. Regular training and staying updated on best practices also help analysts efficiently filter relevant information and produce accurate, actionable intelligence.

What is the difference between Entry Level Open Source Intelligence Analyst vs Cybersecurity Analyst?

AspectEntry Level Open Source Intelligence AnalystCybersecurity Analyst
Required CredentialsBachelor's degree in intelligence, security, or related field; certifications like OSINT certificationsBachelor's in cybersecurity, computer science; certifications like CompTIA Security+ or CEH
Work EnvironmentGovernment agencies, intelligence firms, private securityIT departments, security firms, corporate environments
Industry UsageIntelligence gathering, national security, law enforcementProtecting networks, incident response, threat analysis

While both roles involve security and information analysis, Entry Level Open Source Intelligence Analysts focus on collecting and analyzing publicly available information for intelligence purposes, often within government or security agencies. Cybersecurity Analysts primarily protect digital assets by monitoring and defending networks. The roles share some certifications and work environments but differ in their core focus and industry applications.

What are popular job titles related to Entry Level Open Source Intelligence Analyst jobs in Indiana? For Entry Level Open Source Intelligence Analyst jobs in Indiana, the most frequently searched job titles are:

Mathematical Statistician (Data Scientist) - Direct Hire

Criminal Investigation & Law Enforcement | IRS Careers

Evansville, IN

$74K/yr

Other

Posted 5 days ago


Job description

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

  • Position(s) are to be filled in the following area(s):
    • DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications: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 cut-off dates as shown in announcement under the 'How to Apply' section.
IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist):
You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics, and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.
OR
Combination of education and experience -- includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
GS-1529-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science projects.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR
EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields.
OR
Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.
OR
Combination of education and experience: A combination of qualifying graduate education and experience equivalent to the amount required.
GS-1529-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.

GS-1529-13 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service.
Examples of specialized experience for this position may include:
  1. Experience applying project management principles on a data science project.
  2. Experience planning and executing a variety of data science and/or analytics projects.
  3. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  4. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  5. Experience working with multiple data types and formats as a part of a data science project.
  6. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  7. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  8. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  9. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
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