Data Scientist, Cybersecurity (Audit Readiness)

Hammerjack Pty Ltd; Taguig; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Hammerjack Pty Ltd seeks a Data Scientist to join the IT Audit Readiness team, developing analytics-driven solutions to enhance audit efficiency and risk management. You will partner with auditors and stakeholders to automate manual audit activities across SOX ITGC and HIPAA programs.

The role requires 3–5 years in data analytics or related fields, with strong SQL, Python/R, and visualization skills. Cloud and automation experience is valued. English communication is essential.

Qualifications

• Bachelor's degree in a quantitative field; Master's degree preferred
• 3–5 years hands-on experience in data analytics, data science, BI, audit analytics, or process automation
• Experience supporting Internal Audit, IT Audit, Cybersecurity, Risk, or Compliance functions is strongly preferred
• Professional certifications (CISA, CISSP, CISM, HCISPP, or similar) are an advantage

Responsibilities

• Partner with IT Audit and Compliance teams to apply analytics, automation, and ML to improve audit coverage, efficiency, and risk detection
• Extract, integrate, clean, and analyze data from ERP, HR platforms, cloud environments, security tools, and other enterprise apps
• Design, develop, and maintain data pipelines, SQL queries, data models, and reusable analytics frameworks for continuous monitoring and automated controls testing (SOX ITGC and HIPAA)
• Perform EDA and develop ML models to detect anomalies, trends, and control deficiencies
• Build interactive dashboards and executive reports communicating audit insights and compliance status
• Automate manual audit and compliance processes using data-driven testing and workflow automation
• Evaluate data quality and governance; recommend improvements to processes and data practices
• Translate complex analytical findings into clear, actionable recommendations for audit leadership

Skills

SQL

Python

R

Power BI

Tableau

Azure

Git

VBA

Analytical thinking

Communication skills

Education

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field

Master's degree preferred

Tools

Microsoft SQL Server

Power Automate / Power Apps

Azure

AWS

GCP

Git

Job description

OVERVIEW

As part of the IT Audit Readiness team within Cybersecurity, the Data Scientist develops data-driven solutions that enhance audit efficiency, compliance monitoring, and risk management through analytics, automation, and advanced analytics and automation. This role partners with auditors and business stakeholders to transform manual audit activities into automated, scalable, and insight-driven processes across SOX and HIPAA compliance programs.

KEY RESPONSIBILITIES

• Partners with IT Audit and Compliance teams to identify opportunities where data analytics, automation, and machine learning can improve audit coverage, efficiency, and risk detection.
• Extract, integrate, clean, and analyze data from diverse sources including ERP systems, Active Directory, HR platforms, cloud environments, security tools, and other enterprise applications.
• Design, develop, and maintain data pipelines, SQL queries, data models, and reusable analytics frameworks that support continuous monitoring and automated controls testing for SOX IT General Controls (ITGC) and HIPAA requirements.
• Perform exploratory data analysis (EDA) and develop statistical and machine learning models to detect anomalies, trends, and potential control deficiencies.
• Build interactive dashboards, visualizations, and executive-ready reports that clearly communicate audit insights, risk indicators, and compliance status.
• Automate manual audit and compliance processes using data-driven testing, workflow tools, and continuous monitoring solutions.
• Evaluate data quality and control effectiveness; recommend improvements to governance, processes, and data practices.
• Translate complex analytical findings into clear, actionable recommendations for audit management, compliance leaders, and business stakeholders.

EDUCATION AND WORK EXPERIENCE

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. Master's degree is preferred.
• 3–5 years of hands-on experience in data analytics, data science, business intelligence, audit analytics, or process automation.
• Experience supporting Internal Audit, IT Audit, Cybersecurity, Risk, or Compliance functions is strongly preferred.
• Professional certifications (CISA, CISSP, CISM, HCISPP, or similar) are an advantage.

SPECIALIZED KNOWLEDGE, SKILLS & ABILITIES:

Technical Skills

• Strong proficiency in SQL (Microsoft SQL Server preferred) and experience building data pipelines and data models.
• Hands‑on experience with Python (pandas, NumPy, scikit‑learn) and/or R for data analysis and modeling.
• Experience with data visualization tools such as Power BI or Tableau.
• Familiarity with cloud platforms (Azure preferred; AWS or GCP also valuable).
• Working knowledge of version control (Git) and basic software engineering practices.
• Proficiency in Microsoft VBA (Visual Basic for Applications).

Domain Knowledge

• Understanding of SOX IT General Controls (ITGC), HIPAA Privacy & Security requirements, or similar regulatory frameworks is preferred.
• Experience working with audit, compliance, or cybersecurity teams is highly desirable.

Soft Skills

• Excellent analytical and problem‑solving abilities with strong attention to detail.
• Ability to communicate complex findings clearly to both technical and non‑technical audiences.
• Strong business acumen and the ability to translate data insights into practical recommendations.
• Ability to work independently while collaborating effectively across teams.
• Excellent written and verbal communication skills in English

PREFERRED QUALIFICATIONS:

• Experience with Power Automate / Power Apps or similar automation platforms.
• Exposure to machine learning model development and evaluation
• Knowledge of modern data architecture and data governance practices