Data Scientist -Internal Audit

Key Skills

Data science techniques, Data Visualization, ggplot, Git, Github, GitLab, Java Programming, Machine learning techniques, Natural Language Processing (NLP), PowerBI, Python Programming, QlikView, R Programming, Risk Analytics, SAP, SQL, Statistical modeling, Terabyte scale datasets

Job Description

Synopsys is looking for an experienced Data Scientist to support its data science and analytics initiatives for the Internal Audit (IA) department. IA is part of the Finance function, and works on a variety of projects each year, covering most operational, financial, technology, and regulatory compliance processes.

How we use Data Science

IA uses Data Science to help inform and guide our work and provide greater value to our stakeholders. We routinely design statistical models for outlier detection purposes and apply advanced analytics to data to identify hidden trends and patterns that may help identify both process improvement and risk mitigation opportunities. 

What you will learn

This position offers a unique opportunity to work with a diverse set of stakeholders across the Company (e.g. Sales, Revenue Recognition, Human Resources, Compliance, etc.) and to learn related processes, as we partner with these groups to design and execute data science and analytics projects.

If you are interested in a role where you continue to learn new processes and experiment with machine learning and data science and analytics for financial and internal audit purposes, this is the job for you. 

Your primary responsibilities

• Execute IA data science and analytics projects, including, but not limited to the areas of risk assessment, audit execution, and special projects
• Partner with IA team members to help identify questions and issues for data analytics and experiments across a variety of projects
• Collaborate with appropriate stakeholders and partners to execute projects from design to delivery
• Experiment and implement proofs of concepts across multiple processes / datasets
• Design and implement scripts that cleanse, integrate, and evaluate large datasets from multiple disparate sources, apply statistical analytics, and use machine learning where appropriate, to extract insights for auditors and other partners
• Create visualizations, including dashboards, to display data-backed insights and predictive results
• Engage with team members to promote, adhere to, and contribute to continually improving the team’s data science standards and processes, including code check-in and version control, as well as creating and maintaining appropriate documentation
• Communicate and explain one’s work and results to stakeholders
• Continually learn and develop applicable technical and professional skills
• Mentor junior data scientists, analysts, and audit staff
• Develop professional relationships within the team and across the organization

What We Require

• Bachelor's degree in statistics, mathematics, computer science, or other related field and 2+ years professional experience; Advanced degree preferred
• Experience applying statistical modeling, machine learning (ML/AI) algorithms for supervised & unsupervised learning, and natural-language processing (NLP) to business problems and goals
• Experience building predictive models using R or Python
• Experience manipulating large datasets using R, Python, or SQL
• Experience with data visualization tools, such as Tableau, PowerBI, Qlikview, ggplot, etc.
• Excellent communications skills, including the ability to simplify recommended action plans from complex data science projects
• Experience using git (GitLab/GitHub), or other software development version control system, preferred
• Familiarity using SAP and Salesforce a plus, but not required
• Experience using data science and analytics for auditing purposes a plus, but not required