Compliance and Ethics Data Analytics Specialist

 

 

Location:   Romania/Bucharest  Working arrangement: Hybrid

 

 

The Opportunity
The Compliance and Ethics Data Analytics Specialist is responsible for all primary data analysis and data reporting for the global compliance and ethics team. The incumbent will provide support for ethics and compliance programs related to data analysis, compliance risk assessments and remediation, Key Process Indicators (KPIs), dashboard development and monitoring, and surveys.

 

Main Duties and Responsibilities
 

• Lead the compilation, analysis, and communication of data related to Compliance and Ethics programs (including reporting out to the Compliance and Ethics team, business leaders, and legal teams as necessary).
• Use multiple advanced analytical and statistical techniques (such as natural language processing, time-series modeling, predictive modeling, valuation of options and derivatives, sampling, sample size calculations, hypothesis testing, and/or A/B testing).
• Provide business intelligence, analysis, and data-related compliance information in support of the development/implementation of regulatory and compliance policies, programs, processes and tools.
• Work with Compliance Officers to develop compliance metrics, monitoring, and dashboards to support effective oversight of the business operation's compliance with regulatory requirements and improved risk management.

 

To Join Our Team, You Will Need
 

• 3 or more years of compliance, audit, or business experience
• Data science-specific certifications, that could include one of the following:

- Certified Analytics Professional (CAP)

- Data Science Counsel of America (DASCA) Senior or Principal Data Scientist

- IBM Data Science Professional Certificate

- Microsoft Certified: Azure AI Fundamentals or Azure Data Science Associate

- Open Certified Data Scientist (Open CDS)

- SAS Certified: AI and Machine Learning Professional, Advanced Analytics Professional using SAS 9, or SAS Certified Data Scientist

• Proficiency with Microsoft Office (PowerPoint, Excel, and Spreadsheets) and data gathering/analysis tools, information analysis/synthesis, and database management
• Experience developing monitoring tools, enhancing data visualization tools, model validation, and testing
• Standard data analytics tools and technologies (SQL, R, Python, Tableau, Alteryx, Hadoop, Hive, Spark, Impala, Sqoop, RDBMS, Trifacta)
• Data mining, statistical modeling, machine learning, and other advanced analytics methods
• Strong project, organizational, and time management skills