6 Model Governance Jobs

About this role BlackRock is one of the world s preeminent asset management firms and a premier provider of global investment management, risk management and advisory services to institutional, intermediary, and individual investors around the world. BlackRock s mission is to create a better financial future for our clients. We have a responsibility to be the voice of the investor, and we represent each client fairly and equally. Constant communication with a diverse team of partners strengthens us and delivers better results for our clients. Continuous innovation helps us bring the best of BlackRock to our clients. BlackRock offers a range of solutions from rigorous fundamental and quantitative active management approaches aimed at maximizing outperformance to highly efficient indexing strategies designed to gain broad exposure to the world s capital markets. Our clients can access our investment solutions through a variety of product structures, including individual and institutional separate accounts, mutual funds and other pooled investment vehicles, and the industry-leading iShares ETFs. About Aladdin Financial Engineering (AFE): Join a diverse and collaborative team of over 400 modelers and technologists in Aladdin Financial Engineering (AFE) within BlackRock Solutions, the business responsible for the research and development of Aladdin s financial models. This group is also accountable for analytics production, enhancing the infrastructure platform, and delivering analytics content to portfolio and risk management professionals (both within BlackRock and across the Aladdin client community). The models developed and supported by AFE span a wide array of financial products covering equities, fixed income, commodities, derivatives, and private markets. AFE provides investment insights that range from an analysis of cash flows on a single bond, to the overall financial risk associated with an entire portfolio, balance sheet, or enterprise. Role Overview: We are looking to hire a quantitative modeler (Associate) to join our Portfolio Risk Modeling team. This team builds and maintains risk models and analytics, including linear factor models, Value-at-Risk (VaR) methodologies, volatility and covariance matrix estimation, and portfolio stress testing & scenario analytics. These models span a wide variety of asset classes including fixed income, equity, and private markets. The models utilize sophisticated econometric/statistical methods, and are used by traders, portfolio managers and risk managers at BlackRock and Aladdin clients for risk management, portfolio construction, regulatory reporting, compliance and performance attribution. This individual would have a strong background in quantitative research, have demonstrable project management skills as well as proven experience to work in a team environment as well as collaborating with senior modelers from other groups/regions. This person is expected to join as an individual contributor and deliver on all aspects of model governance for our portfolio risk model suite and provide model governance representation to internal stakeholders and Aladdin clients. Key Responsibilities: Contribute to governance for Aladdin portfolio risk models including (but not limited to) equities, fixed income, commodities, derivatives, etc. Building and maintaining model governance controls, including (but not limited to) model performance monitoring, model documentation, model remediations and supporting internal & external client model validations Communicate (verbally and in writing) with internal stakeholders and external clients on model performance regularly, investigate exceptional model performance, diagnose issues and conduct corrective remediations Backtesting, documenting, and guiding new models and methodologies through validation Partner with engineering teams to integrate portfolio risk models into state-of-art production systems Qualification 3-6 years of experience in quantitative field / statistical modeling. Experience with portfolio risk analytics and/or model governance is strongly preferred Advanced degree in a quantitative discipline - master s degree in finance / economics / statistics / financial engineering / math finance, etc. Knowledge of investments, portfolio management, econometrics, and empirical asset pricing A strong background in quantitative research Hands-on experience with statistical software (e.g., Python, R) and strong background in programming. Proficiency with Python is strongly preferred Experience with data handling (ETL, data joining with SQL, cleaning, processing, summarizing, descriptive analysis), and building and back-testing statistical and econometric models Prior work experience in financial modeling (e.g., risk models, analytics, private markets) or data science and model deployment to production environment is a plus Ability to work effectively with a team of highly motivated individuals Time and project management skills Proven track record of guiding junior talent Positive attitude and ability to work both independently and as a part of a global team in a fast-paced environment Excellent communication and presentation skills

Responsibilities The role will be responsible for several key areas: Work with vendors and internal modeling partners to develop approval documentation for new fraud scores and algorithms. This will include a comprehensive write-up on how the models are built, testing and validation work done, methodology, sampling, performance, etc. Conduct periodic model validations on scores, looking for key metrics such as precision, recall, rank ordering of score performance, detection of PSI and other metrics as needed to ensure models are performing well and not deteriorating, which could lead to unexpected fraud losses Partner with our Strategies teams to communicate model performance and trends, including providing key insights into areas where scores are deteriorating or underperforming, so appropriate adjustments can be made to prevent unexpected losses Work with our partners in Model Risk Management (MRM) to close out any follow-up items on partially/conditionally approved models Form strategic partnerships with MRM to develop best practices for fraud model governance that satisfy both the need for quick deployments to mitigate risks, but also our internal and regulatory concerns Develop dashboards and MIS to show model performance, trending, and potential issues Support automation initiatives within the team and try to automate repetitive tasks Requirements Education* Advanced degree, preferably in Statistics/Mathematics, Computer Science, Engineering or other quantitative discipline from a premier institute Certifications If Any Technical certifications in SAS, SQL preferred Foundational skills* 6 to 9 years of relevant experience in analytics, with around 2+ year of direct experience in model risk management. Experience with model development and fraud analytics are preferred Experience in SAS or SQL is required. Knowledge of Python/PySpark is strongly preferred. Should also have experience with other data extraction tools like Hive, HUE, or Pig. Proficiency with visualization software such as Tableau and presentation software such as PowerPoint Excellent communication and organizational skills Ability to think outside the box and excellent drive/desire to dig in, learn and make a difference Desired skills Bachelors degree preferably in a quantitative discipline such as mathematics, statistics, engineering, computer science, finance, or business. Post graduate degree is a plus. U.S financial services experience preferable Understanding of business domains like Fraud/Compliance/Risk preferable Shift Timings: 11 30 AM to 8 30 pm Location: Chennai If interested, apply on the below link - https://ghr.wd1.myworkdayjobs.com/lateral-ba_continuum/job/Gandhinagar/Manager_25017698

In this role, you will: Participate in less complex analysis and modeling initiatives, and identify opportunity for process production, data reconciliation, and model documentation improvements within Risk Management Review and analyze programing models to extract data, and manipulate databases to provide statistical and financial modeling, and exercise independent judgment to guide new and existing projects with medium risk deliverables Coordinate and consolidate the production of monthly, quarterly, and annual performance reports for more experienced management Present recommendations for resolving data reconciliation, production, and database issues Exercise independent judgment while developing expertise in policy governance, risk projects, and regulatory requests Collaborate and consult with peers, managers, experienced managers, compliance, including various lines of business Required Qualifications: 2+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desires Qualifications: Experience in Loss Forecasting, CCAR Reporting, Stress testing or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Expertise in few programming and statistical packages - SAS, SQL Advanced expertise in MS office tools including Excel and Powerpoint Desired Qualifications: Strong analytical and problem-solving skills with keen attention to detail Model review and ability to analyze and challenge model parameters and assumptions Understand business objectives and provide challenge to requirements. Knowledge and understanding of credit risk, loss forecasting, and related governance policies. Verify sound analysis practices and data decisions were leveraged throughout planning and data sourcing phases. Conduct in-depth research within complex data environments to identify data integrity issues and propose solutions to improve accuracy. Ensure comprehensive documentation exists supporting the end-to-end data reporting and analysis approach and execution. Understanding of complex databases and ability to navigate and query data effectively. Apply critical evaluation to challenge assumptions, formulate a defendable hypothesis, and ensuring high quality results. Ensure adherence to data management/ model governance regulations and policies. Ensure adherence to compliance and legal regulations and policies on all projects managed Collaborate and consult with peers, colleagues, and more experienced managers to resolve issues and achieve goals. Understanding in Python, Tableau, PowerBI will be an added advantage. Job Expectations: Lead or participate in moderately complex initiatives, and delivering insight and decision strategies within Loss Forecasting, and contribute to Loss Forecasting submissions Review and analyze moderately complex data aggregation, forecasting, reporting, and programming models. Review Loss Forecasting quantitative and qualitative models Be responsible for process production, data reconciliation, and model documentation in alignment with policy governance Resolve data, production, business modeling, and lead team to meet Loss Forecasting deliverables while leveraging solid understanding of risk reporting policies, modeling strategies, procedures, regulatory requests, and compliance requirements Collaborate and consult with peers, experienced managers, compliance, and technology to resolve modeling, forecasting, and production issues, and achieve analytic and reporting goals within tight deadlines Partner with cross enterprise risk analysts in development of common modeling strategies

Role Title: AVP, Transaction Fraud Strategy and Model Governance Company Overview: Synchrony (NYSE: SYF) is a premier consumer financial services company delivering one of the industrys most complete digitally enabled product suites. Our experience, expertise and scale encompass a broad spectrum of industries including digital, health and wellness, retail, telecommunications, home, auto, outdoors, pet and more. We have recently been ranked #2 among India’s Best Companies to Work for by Great Place to Work. We were among the Top 50 India’s Best Workplaces in Building a Culture of Innovation by All by GPTW and Top 25 among Best Workplaces in BFSI by GPTW. We have also been recognized by AmbitionBox Employee Choice Awards among the Top 20 Mid-Sized Companies, ranked #3 among Top Rated Companies for Women, and Top-Rated Financial Services Companies. Synchrony celebrates ~52% women diversity, 105+ people with disabilities, and ~50 veterans and veteran family members. We offer Flexibility and Choice for all employees and provide best-in-class employee benefits and programs that cater to work-life integration and overall well-being. We provide career advancement and upskilling opportunities, focusing on Advancing Diverse Talent to take up leadership roles Organizational Overview: Credit Team decisions credit actions across the lifecycle of a customer – from acquisition to account management to collections and recover – we work towards managing credit and fraud losses and elevating customer experience through powerful and proprietary insights on customer risk and credit behaviours. The actionable insights are driven by access to numerous alternative data sources, new age technologies, focused strategies, emerging algorithms, and predictive precision. Spread across 10 pillars the credit team in India caters to the entire gamut of decision sciences, from data management to model development to strategy design, and bringing it all to life through technology, and managing within the guardrails of our regulatory requirements. As part of the team, you will have access to some unique product propositions, functional and leadership training, interaction with executive leadership team and a myriad of diverse perspectives. Role Summary/Purpose: The AVP, Transaction Fraud Strategy and Model Governance is a multifunctional role within Transactional fraud strategy team with several key responsibilities. The primary responsibility is to perform analytic deep dives and root cause analysis to diagnose the impact of transactional fraud model scores performance on transactional fraud strategies. The role will work closely with the Model Developers as well as the Fraud Strategy team to create remediation plans when models used in fraud strategies are not performing as expected. Additional responsibilities will include development of action plans and playbook to address Model issues and MRA’s. Documentation of model development, model development testing and audit responsibilities to ensure proper model implementation in Advance Defense, SAS FM, RAMS, etc. This role will utilize advanced analytical tools to investigate strategy performance and to build new Fraud strategies. This position is remote, where you have the option to work from home. On occasion we may request for you to commute to our nearest office for in person engagement activities such as team meetings, training and culture events. We’re proud to offer you choice and flexibility Key Responsibilities: As part of on-going model monitoring, work closely with on-shore counterpart to perform deep dives and root cause analysis when models used in the transactional fraud strategies have red segments to determine the impact on fraud strategies. Provide support for Model Swaps / Use and Performance in Strategies / Model and Tool Innovation / Model and Strategy Analytics/Model implementation validations and ensure strategies have the use of the best available tools and scores. Support to assess and evaluate potential new models and tools to determine their suitability, and subsequently onboard them into existing systems or workflows (Visa Compromise Score, VDA, MC Card Disruptor, Signifyd etc..) Create a comprehensive playbook and detailed action plans to effectively address any issues related to models and MRA’s and develop detailed documentation to support the strategy team’s model development process to ensure consistency, transparency, and alignment with organizational goals. Collaborate with 2nd / 3rd line to ensure strong governance, safety & soundness of strategies. Fully support regulatory requests, internal reviews, audits and business continuity planning Assist in the development of robust fraud prevention strategies and conduct in-depth analytics to identify trends, risks, and vulnerabilities to enhance detection and mitigation efforts as well as managing few critical process. Work closely with implementation team to ensure that Transactional Fraud Strategic goals are met and remove obstacles to meeting those goals. Support the ideation, analysis, evaluation and integration new data and scores into the strategy framework Support the creation processes & controls to ensure that data, analyses, strategies, and recommendations are accurate. Perform ad hoc analytics, validations, remediations as required Required Skills/Knowledge: Bachelor's degree with quantitative underpinning (i.e., Risk, Economics, Finance, Mathematics, Statistics, Engineering) with minimum 4 & above years' in building analytically derived strategies within Credit, Marketing, Risk or Collections in Financial services, or in lieu of a degree 6 & above years' of relevant experience in an analytical/quantitative role related to consumer lending. 4+ years of experience working with statistical tools such as SAS, Python, Model Builder Decision Tree, Knowledge Seeker or others. Expert level proficiency with Excel Excellent temperament and ability to work through uncertainty, collaborate respectfully across functions & teams, and find solutions to issues Desired Skills/Knowledge: Experience operating as part of a cross functional team Experience analyzing large data sets to derive strategies, segmentations, actionable insights Ability to conduct advanced data extraction, data merging and data analysis using large datasets and complex algorithms Experience using advanced modeling & data mining techniques (e.g. decision trees) to develop/ optimize fraud strategies Understanding of credit and fraud models and their use in fraud strategies Understanding of the Lines of Defense (2nd Line Strategy Validation and 3rd Line Internal Audit) Familiarity with consumer and commercial lending products and practices Good communication & presentation skills and the ability to effectively provide insights, solicit feedback and problem solve with peers Experience with model governance processes and model validation. Eligibility Criteria: Bachelor's degree with quantitative underpinning (i.e., Risk, Economics, Finance, Mathematics, Statistics, Engineering) with minimum 4 & above years' in building analytically derived strategies within Credit, Marketing, Risk or Collections in Financial services, or in lieu of a degree 6 & above years' of relevant experience in an analytical/quantitative role related to consumer lending. Experience using advanced modeling & data mining techniques required. 4+ years of experience working with statistical tools such as SAS, Python, Model Builder Decision Tree, Knowledge Seeker or others. Work Timings: 2PM - 11PM IST

Lead Portfolio Analytics & Model Governance Designation Lead Grade DGM Reporting to Head – Risk Analytics Location Mumbai (Vikhroli) Function Analytics Job Purpose The role will be responsible to provide data driven approaches towards informed decision making to manage the lending portfolio, analytics across the customer lifecycle and facilitate model governance Job Description The role will be responsible for managing two functional areas: 1. Portfolio Analytics 2. Model Governance Portfolio Analytics: • Lead a team to identify and evaluate risks associated with the overall portfolio across multiple lending products for all Godrej Capital companies • Participate and drive the analytics viewpoint in senior management forums across all lending products, • Responsible to provide detailed analyses that allow actionable policy changes by building accurate and automated monitoring tools • Deep dive into portfolio performance using traditional and nontraditional data visualization methods on in-house performance data as well as external datasets like bureau scrub, pan India market insights etc. Model Governance: • Ensure all models used are validated and monitored as per the model governance framework and relevant regulatory guidelines • Lead discussions with internal and external stakeholders to facilitate model governance activities, identify potential risks associated with model use through automated monitoring and developing mitigation strategies Qualification & experience • Qualifications – B.Tech / M.Tech / MBA • Experience in SQL, Python, R, Tableau. Knowledge of Statistical Models and applications of AI will be an added advantag

Looking profiles with Experience in ~ Model Risk Governance, Assurance, Internal Controls, Audit, Risk Management , Risk Governance Required Candidate profile Pls share your CV at jatin@smrd.in