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Job description
The Associate Manager, Compliance Analytics supports the development and implementation of compliance analytics across the global compliance organization to design and develop analytical solutions, generate insights, and promote a culture of ethics and integrity. This position will design and deliver analytics solutions that would include transforming data from multiples system, designing the analytics approach and executing the analytics.
What you will do:
- Design, develop, and maintain analytics to provide business insights, enable risk-intelligent decisions, inform the compliance risk assessment process, and support remediation activities.
- Scope, gather requirements, develop analytics model, validate and test models, and communicate results to stakeholders for analytics projects
- Support execution of analytics initiatives to support the Global Compliance program and provide actionable insights through data and analysis to achieve business objectives.
- Support the development of standardized analytics processes and frameworks, including documentation and validation of work and Set-up sustainable analytics solutions, including data pipelines and automated refresh schedules, if required.
- Collaborate with compliance officers, IT and stakeholders to understand business objectives, and provides reliable and accurate reports, insights, and analysis to inform decision-making
- Lead culture of continuous improvement by enhancing existing databases, data collection methods, statistical methods, technology, procedures, and training.
- Partner with data custodians and process experts to ensure quality of data and definitions to support building reliable data models and analysis.
- Coach and develop junior team members.
What you will need:
- 8+ years of relevant work experience in Python, Advanced SQL, R, Azure, Databricks, PySpark, and PowerBI.
- Strong knowledge & experience in advance analytics tools and languages to analyze large data sets from multiple data sources
- BTech in Computer Science, IT, MSc in Mathematics/Statistics or equivalent courses from accredited university required.
- Strong understanding of algorithms, mathematical models, statistical techniques, data mining, like regression models, clustering/ segmentation, time series forecasting, decision trees/random forest, etc.
- Data science background with experience implementing statistical, machine learning models.
- Experience with analyzing accounting and other financial data.
- Demonstrates excellent ability to exercise discretion and maintain confidentiality.
- Knowledge and experience with data transformation and cleansing, data modeling and database concepts