Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Description The ADSP provides entry-level talent with practical work experience through project ... forensic action against a variety of threats to Apple's ecosystem. • Apply data science to core ...
Entry Level Forensic Accounting information
See Texas salary details
$57.1K is the 25th percentile. Wages below this are outliers.
$53.1K - $61.2K
51% of jobs
$61.2K - $69.4K
11% of jobs
$75.4K is the 75th percentile. Wages above this are outliers.
$69.4K - $77.5K
19% of jobs
$77.5K - $85.6K
5% of jobs
$85.6K - $93.8K
4% of jobs
$93.8K - $101.9K
0% of jobs
$101.9K - $110K
1% of jobs
$110K - $118.2K
2% of jobs
$118.2K - $126.3K
3% of jobs
$126.3K - $134.4K
2% of jobs
$134.4K - $142.5K
2% of jobs
$53.1K
$79.4K
$142.5K
How much do entry level forensic accounting jobs pay per year?
As of Jul 26, 2026, the average yearly pay for entry level forensic accounting in Texas is $79,355.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,400.00 and $79,200.00 per year, depending on experience, location, and employer.
Will AI replace forensic accountants?
Forensic accountants analyze financial data to detect fraud and financial crimes, and while AI can automate routine tasks like data analysis and pattern recognition, it is unlikely to fully replace the critical thinking, judgment, and investigative skills required in forensic accounting. Professionals will increasingly use AI tools to enhance efficiency but will still need human expertise for complex cases and ethical considerations.
What is the difference between Entry Level Forensic Accounting vs Entry Level Auditing?
| Aspect | Entry Level Forensic Accounting | Entry Level Auditing |
|---|---|---|
| Certifications | Often requires CPA or CFE | Typically CPA or equivalent |
| Work Environment | Investigative, legal, and financial settings | Corporate, public accounting firms, or internal audit teams |
| Industry Usage | Legal cases, fraud investigations, litigation support | Financial statement verification, compliance, internal controls |
Entry Level Forensic Accounting and Entry Level Auditing share common certifications like CPA and work in financial environments. However, forensic accounting focuses on investigations and legal cases, while auditing emphasizes verifying financial statements and compliance. Both roles are essential in the finance industry but serve different purposes and require specialized skills.
What are some common challenges faced by entry-level forensic accountants, and how can they effectively overcome them?
Entry-level forensic accountants often encounter challenges such as analyzing large volumes of complex financial data, learning to use specialized forensic software, and understanding the legal standards required for evidence. To overcome these hurdles, new professionals benefit from strong mentorship, ongoing training, and active collaboration with experienced colleagues. Developing effective communication skills is also crucial, as forensic accountants frequently work with legal teams and may need to present findings clearly to non-accountants.
What are the key skills and qualifications needed to thrive as an Entry Level Forensic Accountant, and why are they important?
To thrive as an Entry Level Forensic Accountant, you need a solid foundation in accounting principles, analytical thinking, and a bachelor's degree in accounting or a related field. Familiarity with accounting software, data analysis tools like Excel, and knowledge of fraud detection techniques or certifications such as CFE (Certified Fraud Examiner) are often beneficial. Strong attention to detail, integrity, and effective communication skills help you analyze complex data and present findings clearly. These competencies are crucial for detecting financial discrepancies, supporting investigations, and ensuring accurate and ethical reporting.
What is entry level forensic accounting?
Entry level forensic accounting refers to positions for individuals who are new to the field of forensic accounting, typically requiring a bachelor’s degree in accounting or a related field. These roles involve assisting with investigations of financial fraud, analyzing financial records, and preparing reports for legal proceedings. Entry-level forensic accountants often work under the supervision of senior accountants or investigators, gaining practical experience in both accounting principles and investigative techniques. This position is a common starting point for those interested in a career that combines accounting skills with detective work.
Do I need a CPA to be a forensic accountant?
A CPA license is not required to become a forensic accountant, but it can enhance credibility and job prospects. Many forensic accountants hold accounting degrees and certifications such as the Certified Fraud Examiner (CFE) or Certified Forensic Accountant (Cr.FA), and strong skills in accounting, auditing, and investigation are essential.
Is it easy to get a job in forensic accounting?
Entry level forensic accounting positions can be competitive, but having relevant education such as a degree in accounting or finance, along with certifications like the Certified Fraud Examiner (CFE), can improve job prospects. Gaining experience through internships and developing skills in auditing, data analysis, and forensic tools also enhance employability in this field.
How to start in forensic accounting?
To start in forensic accounting, obtain a bachelor's degree in accounting, finance, or a related field, and develop strong analytical and investigative skills. Gaining relevant certifications such as the Certified Fraud Examiner (CFE) or Certified Public Accountant (CPA) can enhance job prospects, and gaining experience through internships or entry-level accounting roles is beneficial.
What are the most commonly searched types of Forensic Accounting jobs in Texas? The most popular types of Forensic Accounting jobs in Texas are:
What cities in Texas are hiring for Entry Level Forensic Accounting jobs? Cities in Texas with the most Entry Level Forensic Accounting job openings:
Full-time
Posted 5 days ago
Apple rating
8.0
Based on 675 frontline employees who took The Breakroom Quiz
7th of 30 rated technology retailers
Job description
Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
Join the Applied Data Solutions Program (ADSP) and make a positive impact on one of the most influential technology leaders in the industry. You'll be tasked with building sophisticated, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. You will work with teams across Apple, using data analysis and predictive modeling techniques, to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
Description
The ADSP provides entry-level talent with practical work experience through project-based rotations on various teams within Finance. Upon completion, ADSPs move into non-rotating technical roles within Apple. We have a variety of opportunities for software engineers, data scientists, and machine learning engineers. Responsibilities may include:
• Support our business partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency.
• Work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of scalable, easy-to-use systems and tools.
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc.
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions.
• Develop self-service tools and automation to improve data engineering efficiency and self-service analytics.
• Create reporting and monitor decisioning quality to maintain operational and business metric health.
• Translate ambiguous business problems into technical solutions by working collaboratively with business partners.
• Develop, deploy, and operationally support machine-learning models that take real-time and forensic action against a variety of threats to Apple's ecosystem.
• Apply data science to core finance processes to automate and elevate capability, forecasting, accruals, accounting entries prep, IA process, risk mitigation, etc.
Minimum Qualifications
Undergraduate or graduate degree in Computer Science, Data Science, Data Analytics, Machine Learning or related field.
Proficient in at least one programming language (Python/Scala/Java preferred).
Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions.
Practical experience (acquired through work, independent projects, or academic research) with implementing data science-related applications in a programming language such as Python, Scala, or Java.
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions.
Previous Apple FDP or ADSP internship is required.
Preferred Qualifications
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training environments).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Join the Applied Data Solutions Program (ADSP) and make a positive impact on one of the most influential technology leaders in the industry. You'll be tasked with building sophisticated, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. You will work with teams across Apple, using data analysis and predictive modeling techniques, to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
Description
The ADSP provides entry-level talent with practical work experience through project-based rotations on various teams within Finance. Upon completion, ADSPs move into non-rotating technical roles within Apple. We have a variety of opportunities for software engineers, data scientists, and machine learning engineers. Responsibilities may include:
• Support our business partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency.
• Work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of scalable, easy-to-use systems and tools.
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc.
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions.
• Develop self-service tools and automation to improve data engineering efficiency and self-service analytics.
• Create reporting and monitor decisioning quality to maintain operational and business metric health.
• Translate ambiguous business problems into technical solutions by working collaboratively with business partners.
• Develop, deploy, and operationally support machine-learning models that take real-time and forensic action against a variety of threats to Apple's ecosystem.
• Apply data science to core finance processes to automate and elevate capability, forecasting, accruals, accounting entries prep, IA process, risk mitigation, etc.
Minimum Qualifications
Undergraduate or graduate degree in Computer Science, Data Science, Data Analytics, Machine Learning or related field.
Proficient in at least one programming language (Python/Scala/Java preferred).
Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions.
Practical experience (acquired through work, independent projects, or academic research) with implementing data science-related applications in a programming language such as Python, Scala, or Java.
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions.
Previous Apple FDP or ADSP internship is required.
Preferred Qualifications
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training environments).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976