4 Model Audit Jobs

As an Industry & Functional AI Decision Science Manager at Accenture, located in Bengaluru, BDC7C, you will be required to have expertise in Risk Analytics. Additionally, experience in financial modeling, valuation techniques, and deal structuring would be beneficial. In this role, you will drive strategic initiatives, manage business transformations, and utilize industry expertise to develop data-driven recommendations aimed at enhancing business performance. Working with the Accenture CFO & EV team under the Data & AI unit, you will have the opportunity to engage with top financial clients globally. You will have access to cutting-edge technologies and resources, collaborating with talented individuals from diverse backgrounds, fostering innovation and pushing the boundaries of business capabilities. Your responsibilities will include providing strategic advisory services, conducting market research, and developing data-driven recommendations. You will be involved in model development, validation, governance, strategy, transformation, and implementation of risk solutions for Accenture's clients. To excel in this role, you must possess strong analytical, problem-solving, and communication skills. You should be able to work independently in client engagements, manage small projects, and guide junior team members. Additionally, you should have a conceptual understanding of risk regulations and experience in statistical techniques, programming languages, and tools such as SAS, R, Python, Tableau, and PowerBI. Ideally, you should hold a Master's degree in a quantitative discipline or an MBA from a top-tier university. Industry certifications such as FRM, PRM, or CFA would be preferred. Excellent communication and interpersonal skills are essential for this position. This role offers the opportunity to work on innovative projects, career growth, and leadership exposure within Accenture.,

Role & responsibilities The role of Auditor involves: Review and assess the model governance, development, validation, documentation, and implementation to evaluate the effectiveness of the scoring, economic capital, rating and other models using statistical, machine learning techniques. Automate audit testing by utilizing a variety of modeling, data analysis, and programming tools. Identifies anomalies, trends, and risks by analyzing large, complex data sets. Ability to evaluate models across multiple functional domains, such as wholesale, retail, fraud, etc. Proficiency with Python/R, SQL Server, SAS, Excel, JIRA, Bitbucket. Opportunity to contribute to one or more areas of audit covering risk function like audit of Credit Risk, Market Risk, Operational Risk, Pillar II, ICAAP, ERM, Fraud Risk as per RBI guidelines. Key Responsibilities Review and assess the model governance, development, validation, documentation, and implementation to evaluate the effectiveness of the scoring, economic capital, and rating models using statistical, machine learning techniques. Drafting of detailed audit reports with assessment details, preparation of supporting workpapers, clearly documenting the observations noted with implications and recommending corrective actions to auditee. Preferred candidate profile A master's degree in Statistics, Mathematics, or related fields. 7 - 12 years of experience in the financial services industry, preferably with model development, validation, model risk audit, data analytics. Understanding of Risk Management processes like Market, Credit , Operational, ALM, Capital adequacy, Fraud is good to have but not essential. Demonstrate good understanding of model risk function. Knowledge of various modelling techniques used in the banking industry. Experienced with various programming languages used in risk modelling. Drafting of detailed audit reports with assessment details, preparation of supporting workpapers, clearly documenting the observations noted with implications and recommending corrective actions to auditee. Coordinating and supporting the Banks compliance team during RBI Audits and other external audits. Good communication (both verbal & written) and inter-personal skills. Ability to work as a part of team and contribute towards team goals.

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Advanced analytics techniques are utilized to help clients optimize operations and achieve strategic goals. In the role of data analysis at PwC, you will concentrate on using advanced analytical techniques to extract insights from large datasets and enable data-driven decision-making. Your responsibilities will include leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. A Fraud/AML Risk Analytics Professional at PwC will be responsible for developing, validating, auditing, and maintaining AI/ML/NLP models for Fraud/AML/Credit risk. Candidates are expected to support financial institutions in meeting jurisdictional regulatory requirements and broader risk management initiatives. Key responsibilities include: - Developing and validating AI/ML/NLP models for Fraud/AML/Credit risk - Supporting financial institutions in meeting regulatory requirements and risk management initiatives - Utilizing advanced analytics techniques to extract insights from large datasets - Leveraging skills in data manipulation, visualization, and statistical modeling - Building meaningful client connections and learning to manage and inspire others - Growing personal brand and deepening technical expertise - Delivering quality work while embracing ambiguity and seeking opportunities to grow Core Skill Requirements: - 3-7 years of experience in Machine Learning/Artificial Intelligence, Natural Language Programming, Statistical/Mathematical modeling, quantitative research, Fraud/AML risk management, or related Credit Risk field - Proficiency in Machine learning algorithms like Random Forest, SVM, Neural Network, etc. - Experience in AML Scenario development, enhancement, and initial threshold setting and tuning - Proficiency in analytical tools such as Python, PySpark, Data Science, and cloud-based analytics - Business knowledge in transaction monitoring system, sanction screening, trade surveillance - Strong knowledge of fraud data analysis, strategy design, and delivery deployment Non-functional Skill Requirements: - Understanding of market trends and demands in the financial services sector - Excellent oral and written communication skills - Solid analytical and problem-solving skills - Process orientation with attention to detail - Industry knowledge of financial products - Willingness to travel to meet client needs Educational Background: - Master's degree or higher in a quantitative discipline - Industry relevant certifications such as CQF, FRM, CFA, CPA are a plus Additional Requirements For Senior Positions: - Consulting skills to structure and conceptualize solutions for complex problems - Experience in leading large risk analytics engagements independently - Ability to support sales pursuits for risk analytics offerings - Strong conceptual understanding of various functional/technical skills - Ability to drive innovation and thought leadership in risk management This role at PwC offers the opportunity to work with cutting-edge technologies and make a significant impact in the field of data analytics and risk management.,

About the Role The candidate should have masters degree in Statistics, Econometrics, or a related quantitative field. Proven experience in Risk Modelling/Model validation and proficiency with statistical modeling software (R’ & SAS) is desired. Key Responsibilities Model Risk specialist, in close collaboration with Risk Audit team members will execute audits and other model risk audit related activities to ensure efficient and high quality audit execution for critical models in use at the Bank. The internal audit role would include the following as part of the day-to-day job: Audit of model development and validation process within the Bank. Updating risk and control matrix and checklist for audits being undertaken. Undertaking detailed walkthrough of the processes being audited and develop data request for the audit Updating of internal audit MIS with the status of audit observations and other actionable emanating to the audit department Assisting in making presentations to senior management and audit committee on the audits undertaken and performance of internal audits Provide necessary support in automating tests used in audit execution for achieving Continuous Control Monitoring (CCM) Qualifications Optimal qualification for success on the job is: • Knowledge of SR 11-7 guidelines and its implementation for the model governance • Experience in development and validation of statistical models in use across banks, primarily for the purpose of Credit underwriting and measurement & management of Credit Risk, Market & ALM Risk, ICAAP & Stress testing etc. • Previous work experience in Risk Analytics or Model Risk team of a bank or Risk advisory team of leading consulting firm with majority of time allocated on developing or validating statistical/econometric models • Proficiency in statistical modeling software ‘R’, Python, SAS & SQL is an added advantage • Excellent written and verbal communication skills Role Proficiencies: For successful execution of the job, a candidate should possess the- Knowledge of relevant Audit Systems Good communication (both verbal & written) and inter-personal skills Strong Excel and database manipulation skills, financial and statistical analysis skills) Ability to manage risk and uncertainty for self and team within a dynamic priority-setting environment Ability to prioritize and make decisions in a fast-paced environment Ability to manage multiple tasks/projects and deadlines simultaneously