Apple
Data Scientist - Internal Audit
Apple, Austin, Texas, us, 78716
Data Scientist - Internal Audit
Austin,Texas,United States
Corporate Functions
Apple is a place where extraordinary people gather to do their best work. If you’re excited by the idea of making a real impact, a career with Apple might be your dream job—just be prepared to dream big! A highly skilled specialist in advanced analytics, you are passionate about turning data into impactful insights and driving creative data science solutions. You are skilled at creating and evaluating analytical models and interactive visualizations. You are a motivated self-starter, thrive in navigating ambiguity, confident in analyzing data from multiple angles, and can effectively build analytical workflows to deliver findings that directly impact the business. If this describes you, then you should consider joining us.
Description
The Internal Audit Department is seeking a Data Scientist to accelerate its data and automation program. In this role, you will work closely with the Data & Automation Lead to innovate and develop data-driven insights that identify risks, unique insights, potential inefficiencies, and identify areas for improvement throughout the organization. You will have the autonomy to identify audit opportunities and be responsible for both supporting and executing audits and special projects using data analytics. You will also play a crucial role in developing a continuous monitoring program over key areas of the organization. This is a high-visibility role on a small team that will provide you an opportunity to contribute to the organization’s control environment while also gaining exposure to many business areas. Professional Skills: - Self-starter, exceptionally curious, can navigate ambiguity and challenges consistently, and enjoys working in a dynamic environment - Strong ability to work collaboratively as a member of the team and with cross-functional partners - Effective at identifying and assessing risks through collaboration with key stakeholders - Able to consistently and thoughtfully evaluate risk areas and thoughtfully challenge hypothesis via data science skills and resources - Strong ability to work in ambiguous scenarios, maintaining a high level of curiosity and a commitment to uncovering new insights, even if setbacks are encountered - Ability to get things done, experience in delivering end-to-end projects - Passionate about understanding and solving problems, drawing insights and visualizing data, and storytelling - Ability to clearly articulate technical details to non-technical audiences - Excellent project management and organizational skills - Ability and desire to share your expertise with others
Minimum Qualifications
5+ years of data science experience
Bachelor’s Degree in Data Science, Statistics, Computer Science, Quantitative Finance or a related field
Key Qualifications
Preferred Qualifications
A solid understanding of data engineering principles is critical as you will often be responsible for acquiring your own data sets and creating your own data models
Strong understanding of data validations and automated monitoring to ensure completeness, accuracy, integrity and consistency in data pipelines
Proven data science and advanced analytics capabilities including data wrangling, feature engineering, and advanced data analysis to identify patterns, trends, and anomalies
Ability to apply statistical models and machine learning algorithms to assess risks and and solve business problems
Knack for investigating potential risks by exploring new datasets and testing hypotheses, ensuring thorough understanding and analysis of potential problem areas
Knowledge of relational database technologies such as Snowflake and user interfaces like Streamlit, Tableau, and Dataiku
Ability to translate business problems into data requirements
Strong proficiency in SQL and Python
Experience with statistical sampling, hypothesis testing, and probability
Knowledge of audit principles and frameworks, accounting, risk management, or compliance is a plus
Industry recognized certification such as Certified Information Systems Auditor (CISA), Certified Internal Auditor (CIA), or one or more Data Science certifications is a plus
Education & Experience
Additional Requirements
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)
Apple Footer
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .
Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.
Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .
Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .
Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .
Austin,Texas,United States
Corporate Functions
Apple is a place where extraordinary people gather to do their best work. If you’re excited by the idea of making a real impact, a career with Apple might be your dream job—just be prepared to dream big! A highly skilled specialist in advanced analytics, you are passionate about turning data into impactful insights and driving creative data science solutions. You are skilled at creating and evaluating analytical models and interactive visualizations. You are a motivated self-starter, thrive in navigating ambiguity, confident in analyzing data from multiple angles, and can effectively build analytical workflows to deliver findings that directly impact the business. If this describes you, then you should consider joining us.
Description
The Internal Audit Department is seeking a Data Scientist to accelerate its data and automation program. In this role, you will work closely with the Data & Automation Lead to innovate and develop data-driven insights that identify risks, unique insights, potential inefficiencies, and identify areas for improvement throughout the organization. You will have the autonomy to identify audit opportunities and be responsible for both supporting and executing audits and special projects using data analytics. You will also play a crucial role in developing a continuous monitoring program over key areas of the organization. This is a high-visibility role on a small team that will provide you an opportunity to contribute to the organization’s control environment while also gaining exposure to many business areas. Professional Skills: - Self-starter, exceptionally curious, can navigate ambiguity and challenges consistently, and enjoys working in a dynamic environment - Strong ability to work collaboratively as a member of the team and with cross-functional partners - Effective at identifying and assessing risks through collaboration with key stakeholders - Able to consistently and thoughtfully evaluate risk areas and thoughtfully challenge hypothesis via data science skills and resources - Strong ability to work in ambiguous scenarios, maintaining a high level of curiosity and a commitment to uncovering new insights, even if setbacks are encountered - Ability to get things done, experience in delivering end-to-end projects - Passionate about understanding and solving problems, drawing insights and visualizing data, and storytelling - Ability to clearly articulate technical details to non-technical audiences - Excellent project management and organizational skills - Ability and desire to share your expertise with others
Minimum Qualifications
5+ years of data science experience
Bachelor’s Degree in Data Science, Statistics, Computer Science, Quantitative Finance or a related field
Key Qualifications
Preferred Qualifications
A solid understanding of data engineering principles is critical as you will often be responsible for acquiring your own data sets and creating your own data models
Strong understanding of data validations and automated monitoring to ensure completeness, accuracy, integrity and consistency in data pipelines
Proven data science and advanced analytics capabilities including data wrangling, feature engineering, and advanced data analysis to identify patterns, trends, and anomalies
Ability to apply statistical models and machine learning algorithms to assess risks and and solve business problems
Knack for investigating potential risks by exploring new datasets and testing hypotheses, ensuring thorough understanding and analysis of potential problem areas
Knowledge of relational database technologies such as Snowflake and user interfaces like Streamlit, Tableau, and Dataiku
Ability to translate business problems into data requirements
Strong proficiency in SQL and Python
Experience with statistical sampling, hypothesis testing, and probability
Knowledge of audit principles and frameworks, accounting, risk management, or compliance is a plus
Industry recognized certification such as Certified Information Systems Auditor (CISA), Certified Internal Auditor (CIA), or one or more Data Science certifications is a plus
Education & Experience
Additional Requirements
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)
Apple Footer
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (Opens in a new window) .
Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .
Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.
Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .
Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .
Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .