201 Model Validation Jobs - Page 3

The Model Validation Senior Specialist role at Deutsche Bank, based in Mumbai, India, falls under the Model Risk Management department. The primary objective is to manage model risk globally by conducting independent model validation, identifying and mitigating model risks, and supporting the overall model risk management framework. This position focuses on validating stress testing models for the CCAR PPNR umbrella within DB USA, necessitating an understanding of various business segments such as Corporate Banking, Private Banking, and Investment Banking. The incumbent will be responsible for tasks including model performance testing, scenario analysis, and developing challenger models. Automation of processes and framework enhancement to drive efficiency is a key aspect of the role. The ideal candidate should have 2-3 years of experience in model development/validation or related areas, with a preference for previous exposure to stress testing (DFAST/CCAR/ICAAP). Knowledge of B/PPNR models across different business lines and familiarity with financial statements analysis will be advantageous. Proficiency in statistical techniques, analytical skills, and experience with software packages like R and Python are essential. Strong communication skills, report drafting abilities, and a background in Mathematics, Statistics, Economics, Engineering, or MBA are preferred. Additionally, holding a CFA/FRM certification or expertise in Business Intelligence tools will be beneficial for the role. Deutsche Bank offers a comprehensive benefits package that includes a competitive leave policy, gender-neutral parental leaves, childcare assistance benefit, sponsorship for industry certifications, and healthcare coverage for employees and dependents. The organization emphasizes training, coaching, and continuous learning to support career progression. The culture at Deutsche Bank promotes responsibility, commercial thinking, initiative, and collaboration, fostering an environment where employees are empowered to excel together every day. For more information about Deutsche Bank and its teams, please visit the company website at https://www.db.com/company/company.htm. The company values diversity and inclusivity, encouraging applications from individuals of all backgrounds to contribute to a positive and fair work environment.,

The Risk Analytics, Modeling and Validation role involves the development, enhancement, and validation of methods for measuring and analyzing all types of risks, including market, credit, and operational. You will be responsible for developing, enhancing, and validating models for measuring obligor credit risk, early warning tools for monitoring credit risk of corporate or consumer customers, and conducting Loss Given Default studies. Additionally, you will develop and maintain key risk parameters such as default and rating migration data, usage given default data, and transition matrices. Your role is vital to the company as it provides a scientific and systematic approach to assessing and mitigating risks, ensuring the company's financial stability, protecting its assets, and supporting its overall business strategy. As a Model Validator, your responsibilities will include performing model validations, annual model reviews, ongoing monitoring reviews, and model limitation remediation reviews for one or more model/product types under the supervision of a Validation Lead. You will provide effective challenge to the model development process, evaluate testing approaches and results, assess ongoing performance monitoring of models, and contribute to regulatory and internal audit related responses. Collaboration with other teams within Risk and the Business will be essential to facilitate compliance with policies, procedures, and guidance. You are expected to be an enthusiastic and early adopter of change, demonstrating curiosity in seeking new ways to overcome challenges and actively applying learning from failures. You will be responsible for challenging yourself and others to communicate alternative views, acting as a change catalyst by identifying where new ideas could benefit the organization, and proactively seeking to understand and act in alignment with organizational decisions. Prioritizing highest-priority work aligned to business goals, streamlining work processes, and taking personal accountability for managing potential risks are also key aspects of this role. The ideal candidate for this role will have 5-8 years of experience in Quantitative Finance, Risk management, Analytics, Model Development, or Model Validation. Strong partnership and teamwork skills, along with the ability to formulate findings clearly and concisely, are essential. Good analytical, creative thinking, and problem-solving abilities are required, as well as proficiency in programming languages like Python, MATLAB, C/C++/C#, VBA, or other coding languages as needed. Knowledge of financial markets and products, qualitative or quantitative model risk management experience, and extensive experience in data analysis and interpretation are preferred qualifications. A Master's degree in a relevant field is required for this position. Strong technical skills in time series analysis, statistics, and econometrics, along with excellent communication, diplomacy, and problem-solving skills, are necessary. The ability to work effectively in a team and independently, manage multiple tasks and deadlines, and identify inconsistencies in data or results to define business issues are also crucial for success in this role. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, please review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster for more information.,

House of Shipping is seeking a high-caliber Data Science Lead to join their team in Hyderabad. With a background of 15-18 years in data science, including at least 5 years in leadership roles, the ideal candidate will have a proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing. Strong expertise in statistical learning, ML architecture, productionizing models, and impact tracking is essential for this role. As the Data Science Lead, you will be responsible for leading enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This position requires a blend of technical leadership and strategic alignment with various business units to deliver measurable business impact. Key responsibilities include defining and driving the data science roadmap across forecasting, route optimization, warehouse simulation, inventory management, and fraud detection. You will work closely with engineering teams to architect end-to-end pipelines, from data ingestion to API deployment. Proficiency in Python and MLOps tools like Scikit-Learn, XGBoost, PyTorch, MLflow, Vertex AI, or AWS SageMaker is crucial for success in this role. Collaboration with operations, product, and technology teams to prioritize AI use cases and define business metrics will be a key aspect of the job. Additionally, you will be responsible for managing experimentation frameworks, mentoring team members, ensuring model validation, and contributing to organizational data maturity. The ideal candidate will possess a Bachelor's, Master's, or Ph.D. degree in Computer Science, Mathematics, Statistics, or Operations Research. Certifications in Cloud ML stacks, MLOps, or Applied AI are preferred. To excel in this role, you should have a strategic vision in AI applications across the supply chain, strong team mentorship skills, expertise in statistical and ML frameworks, and experience in MLOps pipeline management. Excellent business alignment and executive communication skills are also essential for this position. If you are a data science leader looking to make a significant impact in the logistics industry, we encourage you to apply for this exciting opportunity with House of Shipping.,

The Risk Analytics, Modeling and Validation role involves the development, enhancement, and validation of methods for measuring and analyzing all types of risks, including market, credit, and operational. In areas related to credit risk, individuals in this role develop, enhance, and validate models for measuring obligor credit risk, or early warning tools that monitor the credit risk of corporate or consumer customers, besides being involved in Loss Given Default studies. They also develop and maintain key risk parameters like default and rating migration data, usage given default data and transition matrices. This role is vital to the company as it provides a scientific and systematic approach to assessing and mitigating risks, thereby ensuring the company's financial stability, protecting its assets, and supporting its overall business strategy. The responsibilities of a Model Validator include performing model validations, annual model reviews, ongoing monitoring reviews (on Low and Medium Model Risk Rating (MRR) models) and model limitation remediation reviews for one or more model / product types under the supervision of a Validation Lead (VL). The role also involves providing effective challenge to the model development process, evaluating testing approach and results for individual models, assessing ongoing performance monitoring of the models, contributing to regulatory and internal audit related responses, collaborating with other teams within Risk and the Business, assisting with preparing reports and meeting materials, and supporting the process of designing, developing, delivering, and maintaining best-in-class qualitative model validation process standards. The ideal candidate for this role should have 5-8 years of experience in Quantitative Finance, Risk management, Analytics, Model Development or Model Validation. They should possess excellent partnership and teamwork skills, ability to formulate findings clearly and concisely in written form, good verbal communication skills, good analytic and creative thinking abilities, adept at analysis and documentation of results, ability to multi-task and work well under pressure, and deliver results under tight deadlines. Proficiency in programming languages like Python, MATLAB, C/C++/C#, VBA or other coding languages is required, along with knowledge of financial markets and products. Qualitative or quantitative model risk management experience is a plus, along with strong technical skills in time series analysis, statistics, and econometrics. Education requirement for this role is a Master's degree. Key skills required include Analytical Thinking, Business Acumen, Credible Challenge, Data Analysis, Governance, Policy and Procedure, Policy and Regulation, Risk Controls and Monitors, Risk Identification and Assessment, and Statistics. If you are a person with a disability and need a reasonable accommodation to use the search tools and/or apply for a career opportunity, please review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster for more information.,

As a Portfolio Risk - Cards CCAR Model Development Associate within the Portfolio Risk Modeling team, you will have the opportunity to support and develop regulatory models, execute and prepare model surveillance, and provide insights for various regulatory requirements. You will use your expertise in performance assessment methods and metrics for various types of risk models used in portfolio Risk, regulatory modeling, and forecasting methods. You will be responsible for the development of stress test models as part of the annual CCAR/CECL exercise. This role will allow you to utilize your experience with econometric/statistical modeling, data manipulation, query efficiency techniques, reporting, and automation. We value intellectual curiosity and a passion for promoting solutions across organizational boundaries. Job Responsibilities: Design, develop, test, and validate statistical models for Cards Unsecured Lending portfolio risk forecast and model performance monitoring Utilizing graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, multivariate analysis, discriminant analysis, time series analysis, panel data analysis, Survival Hazard Rate Models etc. Efficiently design and produce programs to streamline and create repeatable procedures for model development, validation, and reporting Process, cleanse, and verify the integrity of data used for analysis Perform deep dive analysis to address ad hoc inquiries Required qualifications, capabilities, and skills MS, Engineering or PhD degree in a quantitative discipline Minimum 6+ years of hands-on work and research experience of advanced analytical skills in the areas of statistical modeling and data mining Proficiency in advanced analytical languages such as SAS, R, Python, PySpark Experience utilizing SQL in a relational database environment such as DB2, Oracle, or Teradata Ability to deliver high-quality results under tight deadlines Strong multi-tasking skills with demonstrated ability to manage expectations and deliver results Preferred qualifications, capabilities, and skills Knowledge of regulatory modeling (IFRS9/CECL/CCAR preferred)

As part of the firm s model risk management function, the Model Risk Governance and Review group is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model's appropriate usage in the business context, evaluating ongoing model performance testing and ensuring that model users are aware of the model strengths and limitations. As a Quant Modelling Analyst, you will be a member of the Model Risk Governance and Review group in Mumbai covering Market Risk models where you will have exposure to multiple assets classes, advanced modelling methodologies as well as day-to-day interaction with Quantitative Research teams and other Risk Functions. Your position will focus on the following activities Job responsibilities Model validation of market risk models - Evaluate conceptual soundness of model specification, the appropriateness of the methodology for its intended purpose, reasonableness of assumptions and reliability of inputs, assessment of model limitations, completeness of testing performed to support the correctness of the implementation. Perform ongoing performance monitoring tests to ascertain that models are relevant and fit for purpose. Assist with model governance processes, model inventory and issue management and help to devise new model governance policies as and when required. Work closely with model developers and controls functions across the firm to understand methodology, usage and establish transparency around model controls, model limitations and performance. Required qualifications, capabilities and skills Quantitative background with at least a Bachelor/Masters/PhD degree inStatistics, Mathematics, Engineering, Quant Finance, or similar. Strong quantitative, analytical, and problem-solving skills; domain expertise in market risk VaR models, derivatives pricing models; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods and stochastic calculus. Strong communication and interpersonal skills; ability to multi-task and meet deadlines. Ability to work independently, with remote supervision. Risk and control mindset ability to ask incisive questions, assess materiality and escalate issue Understanding of Market Risk BASEL/FRTB regulations. Preferred qualifications, capabilities and skills Knowledge and interest in Python programming. Understanding of finance industry, particularly in modeling - valuation, risk, capital, forecasting, investment management.

As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class. MRGR is a global team of modeling experts within the firm s Risk Management and Compliance organization. The team is responsible for conducting independent model validation and model governance activities to help identify, measure, and mitigate Model Risk in the firm. The objective is to ensure that models are fit for purpose, used appropriately within the business context for which have been approved, and that model users are aware of the model limitations and how they could impact business decisions. Being part of the MRGR team will put you at the center of the firm s model validation and governance activities with exposure to a wide variety of model types and cutting edge modeling techniques, while frequently interacting with the best and brightest in the firm. You will expand your knowledge of the different forecasting models used in the firm, their unique limitations, and use that knowledge to help shape business strategy and protect the firm. The successful candidate will head the MRGR Data Science Group in Bangalore, managing a team of junior reviewers. This group will perform the following model risk management activities for Data Science models in the firm Set standards for robust model development practices and enhance them as needed to meet evolving industry standards Evaluate adherence to development standards including soundness of model design, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics Identify weaknesses, limitations, and emerging risks through independent testing, building of benchmark models, and ongoing monitoring activities Communicate risk assessments and findings to stakeholders, and document in high quality technical reports Assist the firm in maintaining (i) appropriateness of ongoing model usage, and (ii) the level of aggregate model risk within risk appetite Minimum Skills, Experience and Qualifications A Ph.D. or masters degree in a Data Science oriented field such as Data Science, Computer Science or Statistics, is required 7+ years of experience in a quantitative modeling role, such as Data Science, Quantitative Model Development, Model Validation, or Technology focused on Data Science, including hands-on experience with building/testing Machine Learning models Domain expertise in following areas Data Science, Machine Learning and Artificial Intelligence. Knowledge and experience in database interfacing and analysis of large data sets is a plus Strong understanding of Machine Learning / Data Science theory, techniques and tools including Transformers, Large Language Models, NLP, GANs, Deep Learning, OCR, XGBoost, and Reinforcement Learning Proven managerial experience or demonstrated leadership abilities, with a track record of successfully leading and managing quantitative teams Proficiency in Python programming, with experience in the Python machine learning library and ecosystem, including NumPy, SciPy, Scikit-learn, Pandas, TensorFlow, Keras, and PyTorch Understanding of the machine learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop Strong communication skills verbally and particularly in writing, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports Risk and control mindset ability to ask incisive questions, assess materiality of model issues, and escalate issues appropriately Role: Head - Data Science Industry Type: Financial Services Department: Data Science & Analytics Employment Type: Full Time, Permanent Role Category: Data Science & Machine Learning Education UG: Any Graduate PG: Any Postgraduate

Part of the firm's model risk management function, the Model Risk Governance and Review group is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model s appropriate usage in the business context, evaluating ongoing model performance testing and ensuring that model users are aware of the model strengths and limitations. As a Quant Analytics Analyst/Associate you will be a member of the Model Risk Governance and Review group in Bangalore, tasked with validation and governance of quantitative and qualitative models developed primarily within the Corporate Investment Banking (CIB) lines of businesses for the Firm s Capital Stress Testing, Resolution planning, Risk Management, and other processes. CIB Finance models have exposure to multiple assets classes; hence, you will have day-to-day interaction with multiple development teams and Risk functions. Your position will focus on the following activities Job responsibilities Model validation of CIB Finance models - Evaluate conceptual soundness of model specification, the appropriateness of the methodology for its intended purpose, reasonableness of assumptions and reliability of inputs, assessment of model limitations, completeness of testing performed to support the correctness of the implementation. Perform ongoing performance monitoring tests to ascertain that models performance is acceptable and fit for purpose. Assist with model governance processes, model inventory and issue management, and help on ad-hoc tasks, special projects and new initiatives as and when required. Work closely with model developers and controls functions across the firm to understand methodology, usage and establish transparency around model controls, model limitations and performance. Required qualifications, capabilities, and skills Analyst or Associate based on number of years of experience in banking / financial services industry with good understanding of Econometric Modelling. Model Validation and Governance experience is preferred. Advanced degree in Math/Statistics, Finance, Economics, Engineering, or related quantitative discipline. Strong writing, organizational, communication and negotiation skills. Strong quantitative and analytical skill, and keen on independent research & problem solving. Ability to communicate clearly and concisely and collaborate across multiple teams/functions. Self-starter, and can work independently or with minimum supervision. Have risk and control mindset and have an eye for details. Preferred qualifications, capabilities, and skills Knowledge and interest in Python programming. Experience in financial products/markets and regulatory stress testing (CCAR/ICAAP). Role: Business Intelligence & Analytics - Other Industry Type: Financial Services Department: Data Science & Analytics Employment Type: Full Time, Permanent Role Category: Business Intelligence & Analytics Education UG: Any Graduate PG: Any Postgraduate

Part of the firm's model risk management function, the Model Risk Governance and Review group is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model s appropriate usage in the business context, evaluating ongoing model performance testing and ensuring that model users are aware of the model strengths and limitations. As a Quant Analytics Analyst/Associate you will be a member of the Model Risk Governance and Review group in Bangalore, tasked with validation and governance of quantitative and qualitative models developed primarily within the Corporate Investment Banking (CIB) lines of businesses for the Firm s Capital Stress Testing, Resolution planning, Risk Management, and other processes. CIB Finance models have exposure to multiple assets classes; hence, you will have day-to-day interaction with multiple development teams and Risk functions. Your position will focus on the following activities Job responsibilities Model validation of CIB Finance models - Evaluate conceptual soundness of model specification, the appropriateness of the methodology for its intended purpose, reasonableness of assumptions and reliability of inputs, assessment of model limitations, completeness of testing performed to support the correctness of the implementation. Perform ongoing performance monitoring tests to ascertain that models performance is acceptable and fit for purpose. Assist with model governance processes, model inventory and issue management, and help on ad-hoc tasks, special projects and new initiatives as and when required. Work closely with model developers and controls functions across the firm to understand methodology, usage and establish transparency around model controls, model limitations and performance. Required qualifications, capabilities, and skills Analyst or Associate based on number of years of experience in banking / financial services industry with good understanding of Econometric Modelling. Model Validation and Governance experience is preferred. Advanced degree in Math/Statistics, Finance, Economics, Engineering, or related quantitative discipline. Strong writing, organizational, communication and negotiation skills. Strong quantitative and analytical skill, and keen on independent research & problem solving. Ability to communicate clearly and concisely and collaborate across multiple teams/functions. Self-starter, and can work independently or with minimum supervision. Have risk and control mindset and have an eye for details. Preferred qualifications, capabilities, and skills Knowledge and interest in Python programming. Experience in financial products/markets and regulatory stress testing (CCAR/ICAAP). Role: Business Intelligence & Analytics - Other Industry Type: Financial Services Department: Data Science & Analytics Employment Type: Full Time, Permanent Role Category: Business Intelligence & Analytics Education UG: Any Graduate PG: Any Postgraduate

As a Risk Manager/Senior Risk Manager - Model Validation at DWS Group in Bangalore, you will be part of one of the world's leading asset managers with a stellar reputation for excellence globally. DWS offers integrated investment solutions across various asset classes and is known for its stability and innovation in the industry. The Risk platform at DWS is responsible for independent risk oversight, with the Model Risk team focusing on governance and control of various models used in the Firm. As a part of the global Model Risk team, your role will involve validating, testing, and overseeing the usage of models related to Corporate Risk and Investment Risk for Liquid and Illiquid investment strategies. You will have the opportunity to enjoy a range of benefits as part of the flexible scheme at DWS, including best-in-class leave policy, gender-neutral parental leaves, sponsorship for industry certifications, and comprehensive insurance coverage for you and your dependents. Your key responsibilities will include conducting model validations, communicating findings and recommendations to model owners, working closely with Investment teams, participating in independent model reviews, and assisting in building benchmark models and methodologies for testing model assumptions. To excel in this role, you should have previous experience in quantitative risk management, model validation, or model development in the Investments, Consulting, or Banking industry. Strong quantitative skills in Python or C++, a good understanding of valuation methods, capital markets, and risk management are essential. Excellent verbal and written communication skills, along with a post-graduate degree in a quantitative field or relevant industry experience/professional qualification, will be beneficial. DWS Group is committed to providing training and development opportunities, flexible working arrangements, coaching from experts, and a culture of continuous learning to support your career progression. Together, we strive for a collaborative and inclusive work environment where every individual is empowered to excel and contribute to the success of Deutsche Bank Group. For more information about DWS Group and our culture, please visit our company website at https://www.db.com/company/company.htm. We welcome applications from all individuals and promote a positive, fair, and inclusive workplace where diversity is celebrated.,

Embark on your transformative journey as a Quant Analytics Wholesale Credit Risk - Vice President. In this role, you will be responsible for developing best-in-class credit risk models using modern model development frameworks and methodologies. Your primary focus will be on driving an increase in value by creating innovative modeling and analytical solutions that enhance the credit risk management and mitigation process through the utilization of broad data and cutting-edge technology. To excel as a Quant Analytics Wholesale Credit Risk - Vice President, you should possess hands-on coding experience, preferably as a full-stack developer or agile developer. Proficiency in languages such as Python and C/C++ is preferred. Additionally, you must have a solid understanding of Credit Risk concepts including Probability of Default (PD), Loss Given Default (LGD), Exposure of Default (EAD), IFRS9/CECL, and CCAR. Experience in Stress Testing/Scenarios Modeling, Model Development and/or Model Validation, as well as Statistical Modeling (particularly for Wholesale credit book) is essential. Highly valued skills for this role may include holding an Advanced Technical Degree (Master's/PhD or similar) in fields such as Statistics, Engineering, Numerical Analysis, Mathematics, Physics, Econometrics, Financial Engineering, Computer Science, or Financial Mathematics. Relevant certifications like GARP-FRM, PRM, CQF, AI/ML Courses, and Coding and Computer Programming are beneficial. Your performance may be evaluated based on key critical skills essential for success in the role, encompassing risk and controls, change and transformation, business acumen, strategic thinking, digital and technology, and job-specific technical skills. The position is based in Mumbai and entails designing, developing, implementing, and supporting mathematical, statistical, and machine learning models and analytics utilized in business decision-making processes. As a Vice President, your responsibilities will involve designing analytics and modeling solutions for complex business problems, collaborating with technology to specify necessary dependencies, developing high-performing analytics and model solutions, implementing models accurately, providing ongoing support, ensuring conformance to all Barclays Enterprise Risk Management Policies, and maintaining a defined control environment. Expectations for a Vice President include contributing to setting strategy, driving requirements, managing resources and policies, delivering continuous improvements, demonstrating leadership behaviors, advising key stakeholders, managing and mitigating risks, showcasing accountability for risk management, understanding organizational functions, collaborating with other areas of work, and creating solutions based on sophisticated analytical thought. All team members are expected to uphold the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as demonstrate the Barclays Mindset of Empower, Challenge, and Drive in their conduct.,

Job Overview: As a candidate for the role, you will be expected to understand the basics and principles of cat modeling and outputs such as exposure, hazard, geocoding, vulnerability, and financial models. You should possess knowledge of using one or more cat modeling software like RMS, AIR, IF, etc. Your tasks will involve running and analyzing QBE exposures on various modeling software tools such as Risk Modeler, AIR Touchstone, and ELEMENTS based on project requirements and business needs. Additionally, you will be required to comprehend different model profile settings, conduct sensitivity tests, and extract and report results. Understanding the client's exposure and risk perspective to facilitate informed decision-making and becoming familiar with in-house tools will also be part of your responsibilities. Responsibilities: In this role, your responsibilities will include but not be limited to: - Performing model validation and offering recommendations on model usage or necessary adjustments. - Collaborating with internal teams and external data providers to analyze data, including scientific information, claims, and insured exposure. - Contributing to and leading Group projects when necessary, while interacting with various teams globally. - Generating customized reports on exposure and modeled results. - Evaluating re/insurance pricing for individual accounts and product classes. - Analyzing catastrophe reinsurance structures and strategies to support reinsurance placements. - Assisting in analyzing real-time events and extracting insights from post-event reviews. Qualifications and Experience: To be successful in this role, you should possess the following qualifications and experience: - A postgraduate or undergraduate degree, preferably in a quantitative, scientific, or environmental discipline. - Strong analytical and numerical skills to analyze large datasets effectively. - Experience working with re/insurance catastrophe data and/or catastrophe modeling software. - Excellent written and verbal communication skills with the ability to explain technical concepts clearly. - Proactive attitude towards identifying inefficient processes and developing improvements. Desirable Requirements: Additionally, having the following qualifications would be desirable: - Knowledge of commercial insurance and/or the catastrophe modeling industry. - Sound working knowledge of RMS/AIR and other vendor modeling platforms. - Coding experience in a relevant language such as SQL, VBA, R, or C#. - Experience in using mapping software like GIS. Qualifications: A degree in Mathematics, Applied Mathematics, Statistics, Engineering, or Actuarial Science would be beneficial for this role.,

The company Ideapoke is a global, fast-growing start-up with a presence in Bengaluru, Bay Area, Tokyo, and Shanghai. Their software, search, and insights drive innovation for Fortune 500 and Global 2000 companies worldwide. Ideapoke's growth is attributed to its dedicated team, committed to the company's vision and characterized by a strong work ethic and an entrepreneurial spirit. The company values continuous learning, growth, and making a difference, inviting individuals to join their journey. As a Lead Artificial Intelligence at Ideapoke, you will be responsible for collaborating with researchers and engineers across various disciplines to develop advanced data analytic solutions. Your role will involve working on large datasets, mapping business requirements into AI products, and evaluating algorithm performance based on real-world data sets. You will be required to mine data from various sources, design and implement machine learning algorithms, and optimize existing algorithms for accuracy and speed. Additionally, you will be expected to research and implement technical solutions in deep learning for real-world challenges. To excel in this role, you are required to hold a Ph.D., Master's degree, B.Tech, or B.E. in Computer Science, Statistics, Mathematics, Engineering, or related fields. You should possess 10 to 12 years of academic or professional experience in Artificial Intelligence, Data Analytics, Machine Learning, Natural Language Processing, or related areas. Technical proficiency in Python, Java, R, XML parsing, Big Data, NoSQL, and SQL is essential for this position. Moreover, you should have a strong mathematical and statistical background, enabling you to understand algorithms and methods from a mathematical and intuitive perspective. The ideal candidate for this role will be a self-starter with the ability to manage multiple research projects. You should have a flexible approach to learning new skills, be a team player, and possess strong communication skills. Your role will involve establishing scalable and efficient processes for model development, validation, implementation, and large-scale data analysis in a distributed cloud environment. By joining Ideapoke, you will contribute to the company's innovative culture and work towards amplifying success for both the organization and its clients.,

WNS is currently seeking CAT Modeling professionals for their global reinsurance client with expertise in the following skill sets: 1. **Portfolio Modeling:** - Understanding of Cat Modeling process and workflows - Experience in running vendor catastrophe modeling platforms (RMS, AIR, Elements) for insureds and conducting portfolio risk analyses - Knowledge of RMS model scope across peril-regions and cat-modelling four-box principle - Assisting clients in understanding catastrophe risk through analytics - Providing analytical support, developing processes, preparing reports, training team members, and ensuring SLAs are met 2. **Regulatory Reporting:** - Understanding Cat Modeling process and workflows - Running catastrophe modeling platforms for accumulation analysis for reporting needs - Knowledge of RMS EDM-RDM schema and regulatory reports like LCM, RDS Scenarios, etc. - Ability to understand regulatory requirements and deliver accordingly - Providing analytical support, developing processes, ensuring SLAs are met, and communicating with stakeholders 3. **Model Validation:** - Performing model validation, providing recommendations, and working with internal teams and data providers - Contributing to Group projects, producing customized reports, and evaluating re/insurance pricing - Analyzing catastrophe reinsurance structures, supporting placements, and identifying learnings from post-event reviews - Strong analytical and numerical ability, experience with catastrophe data, and excellent communication skills - Desirable requirements include knowledge of commercial insurance, coding experience, and proficiency in Excel 4. **Technical Solution (SQL Query):** - Working as a Catastrophe Modelling Analyst in the Accumulation Management department with the Technical Solutions team - Developing customized tools and databases, maintaining existing tools, and assisting users with technical questions - Testing new functionality, designing new tools, and collaborating with global colleagues on projects - Qualifications include a Bachelor's Degree in Mathematics, Applied Mathematics, Statistics, Operations Research, or Actuarial Science These roles offer a unique opportunity to work with cutting-edge technology and contribute to the digital transformation of the reinsurance industry. If you have the required skills and qualifications, we invite you to be a part of our dynamic team at WNS.,

At Lilly, we are committed to uniting caring with discovery to enhance the quality of life for individuals worldwide. As a global healthcare leader headquartered in Indianapolis, Indiana, we have a workforce of 39,000 employees dedicated to developing and delivering life-changing medicines, advancing disease understanding and management, and contributing to our communities through philanthropic efforts. Our priority is always people, and we are in search of individuals who share our passion for making a positive impact on global well-being. As part of our ongoing efforts to achieve these goals, we are focused on building and internalizing a cutting-edge recommendation engine platform. This platform is designed to facilitate more agile sales and marketing operations by incorporating various data sources, implementing advanced personalization models, and seamlessly integrating with all other Lilly operations platforms. The ultimate aim is to provide tailored recommendations to sales and marketing teams at the individual doctor level, thereby enhancing decision-making processes and elevating customer experiences. Key Responsibilities: - Demonstrate a strong grasp of deep learning models to develop optimized Omnichannel Promotional Sequences for implementation by sales teams - Analyze extensive datasets to identify trends and insights that inform modeling decisions - Ability to translate business challenges into statistical problem statements, propose solution approaches, and consider relevant constraints - Collaborate with stakeholders to effectively communicate analysis findings - Proficiency in pharma datasets and industry knowledge is advantageous - Experience in code refactoring, training, retraining, deployment, testing, and monitoring of ML models for drift - Optimization of model hyperparameters - Willingness to learn new skills, particularly in ML applications for solving business problems Required Qualifications: - Bachelor's degree in Computer Science, Statistics, or related field preferred - 2-6 years of hands-on experience with data analysis, including coding, summarization, and interpretation - Proficient in coding languages like SQL or Python - Prior experience in deploying, evaluating performance, and fine-tuning recommendation engine models using ML techniques (e.g., CNN/LSTM, GA, XGBoost) for healthcare-related industries - Proficiency in Feature Engineering, Feature Selection, and Model Validation on Big Data - Familiarity with cloud technologies such as AWS, including tools like S3, EMR, EC2, Redshift, Glue; experience with visualization tools like Tableau and Power BI is a plus At Lilly, we are dedicated to fostering an inclusive workforce that provides equal opportunities for individuals with disabilities. If you require accommodations to apply for a position at Lilly, please complete the accommodation request form for further assistance. Please note that this form is specifically for accommodation requests related to the application process.,

Are you seeking an exciting opportunity to become part of a dynamic and expanding team in a fast-paced and challenging environment This unique position offers you the chance to collaborate with the Business team to deliver a comprehensive perspective. As a Model Risk Program Analyst within the Model Risk Governance and Review Group (MRGR), your responsibilities include developing model risk policy and control procedures, conducting model validation activities, offering guidance on appropriate model usage in the business context, evaluating ongoing model performance testing, and ensuring that model users understand the strengths and limitations of the models. This role also presents attractive career paths for individuals involved in model development and validation, allowing them to work closely with Model Developers, Model Users, Risk and Finance professionals. Your key responsibilities will involve engaging in new model validation activities for all Data Science models in the coverage area. This includes evaluating the model's conceptual soundness, assumptions, reliability of inputs, testing completeness, numerical robustness, and performance metrics. You will also be responsible for conducting independent testing and additional model review activities, liaising with various stakeholders to provide oversight and guidance on model usage, controls, and performance assessment. To excel in this role, you should possess strong quantitative and analytical skills, preferably with a degree in a quantitative discipline such as Computer Science, Statistics, Data Science, Math, Economics, or Math Finance. A Master's or PhD degree is desirable. Additionally, you should have a solid understanding of Machine Learning and Data Science theory, techniques, and tools, including Python programming proficiency and experience with machine learning libraries such as Numpy, Scipy, Scikit-learn, TensorFlow, and PyTorch. Prior experience in Data Science, Quantitative Model Development, Model Validation, or Technology focused on Data Science, along with excellent writing and communication skills, will be advantageous. A risk and control mindset, with the ability to ask incisive questions, assess materiality, and escalate issues, are also essential for this role. By staying updated on the latest developments in your coverage area, you will contribute to maintaining the model risk control apparatus of the bank and serve as a key point of contact within the organization. Join our team and be a part of shaping the future of model-related risk management decisions.,

Whether you are at the beginning of your career or seeking your next adventure, your journey commences here. At Citi, you will have the chance to enhance your skills and contribute to one of the world's most global banks. We are dedicated to supporting your growth and development right from the start, offering extensive on-the-job training, exposure to senior leaders, and traditional learning opportunities. Additionally, you will have the opportunity to give back to the community through volunteerism. Citi Finance oversees the financial management and related controls of the firm. The team manages and collaborates on key Citi initiatives and deliverables, such as the quarterly earnings process and ensuring compliance with financial regulations. The team consists of chief financial officers who partner with various businesses and disciplines, including controllers, financial planning and analysis, strategy, investor relations, tax, and treasury. We are currently seeking a highly skilled professional to join our team as Vice President, NTMR Lead Analyst - Hybrid based in Mumbai. As a part of our team, we will provide you with the necessary resources to meet your unique needs, empower you to make sound decisions regarding your financial well-being, and help you plan for the future. Citi offers access to a range of learning and development resources to enhance your skills as you progress in your career. We also provide programs to help employees achieve work-life balance, including generous paid time off packages. Moreover, we encourage our employees to volunteer in their communities, with Citi employee volunteers contributing over 1 million hours globally in 2019. In this role, you will be expected to: The Balance Sheet Management Lead Analyst supports the BSM NTMR manager in bank balance sheet management and optimization. This involves balancing financial resources among different priorities, understanding Non-Trading Market Risk, and contributing to achieving Corporate Treasury's balance sheet optimization objectives and Citigroup's strategic goals. Strong communication skills are essential to collaborate with stakeholders across levels. The role involves providing support to the NTMR manager in executing functional strategy and reflecting strategic influence on the business. The Balance Sheet Management Model Governance group is a critical team within Treasury/Balance Sheet Management responsible for maintaining and governing models used to generate Non-Trading Market Risk metrics within Treasury. This team plays a vital role in overall balance sheet management and directly impacts Citigroup's Capital. Key Responsibilities: - Support the Non-Trading Market Manager with BSM's management process, asset allocation, and risk analysis - Enhance BSM's analytics and establish Citi's first-line NTMR management framework - Align governance and management framework for legal entities with risk exposure - Identify and remediate gaps in non-trading market risk and interact with stakeholders to ensure compliance Qualifications and Requirements: - Experience in statistical modeling, econometrics, or model governance in the financial domain - 5 to 7+ years experience in Financial Services, Treasury, and bank liquidity investment portfolio - Knowledge of debt investment securities and non-trading market risks - Understanding of regulatory, compliance, risk management, and financial management Education: - Bachelor's degree in Finance or related field; advanced degree is a plus - Proficiency in Bloomberg, fixed income tools, Python, and database management - Strong presentation and Excel skills - Understanding of accounting and general ledger principles,

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

Role description: Independently manage medium to large projects through the lifecycle and use BA tools proficiently (business requirement documents, functional specification documents, data matrix, Work Flow Diagrams etc.) Run test management processes for medium to large scale projects (Test Strategy/Approach documentation, managing User Acceptance Testing, building test plans and test scenarios, building implementation plans.) Assist our stakeholder businesses with their tactical/strategic solution requirements, services and/or program. Must be able to work with Technology, Risk Management, Risk Middle Office, and Front Office to identify and maximize opportunities that help in delivery of projects and to improve product, service and program business processes. Must have the ability to work with a team and train people on various subjects, structure the project governance model and also work together with regional counterparts to devise induction framework for all the resources entering into the project. Prepare project reports (weekly project update, monthly status update, highlighting risks, resource utilization, analyses trends, recommends adjustments that address or capitalize on these changes.) Run test management processes for medium to large scale projects (Test Strategy/Approach documentation, managing User Acceptance Testing, building test plans and test scenarios, building implementation plans.) Skills, experience, qualifications and knowledge required: Strong understanding of capital market products and derivatives across asset classes Good knowledge of the Market Risk domain with project experience in areas like computation of risk measures (VaR, IRC, ES etc.), management of risk limits, risk reporting etc. Good understanding of the Basel norms, particularly FRTB and Basel 2.5 standards Ability to operate in both agile and waterfall style project methodologies and have an understanding of deliverables required for each methodology Attention to detail and high quality standards of documentation, processes and control environment Experience in the full E2E systems delivery lifecycle (SDLC) Detailed knowledge of all Microsoft Office products, i.e. Word, Excel, Power Point, Project and Visio Proficiency in data analysis, virtualization and BI solutions SQL, Python, Dremio, PowerBI, Alteryx, Tableau etc. Excellent communication, organization, prioritisation and documentation skills Flexibility – adapts effectively to changing plans, domains and priorities; Is open and flexible when faced with changing project constraints Deals comfortably with ambiguity – Stays on target to complete goals regardless of obstacles or adverse circumstances Rigorous follow ups through on all commitments to achieve results Excellent and demonstrable understanding of “best practice” approaches to functional testing especially User Acceptance Testing. Ability to identify any inefficiencies in processes and suggest ideas for automation and/or operating model changes.

Job Description: 1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem b. Improve Model accuracy to deliver greater business impact c. Estimate business impact due to deployment of model 2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge 3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch 5. Experience in using Deep learning models with text, speech, image and video data a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV c. Knowledge of State of the art Deep learning algorithms 6. Optimize and tune Deep Learnings model for best possible accuracy 7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau 8. Work with application teams, in deploying models on cloud as a service or on-prem a. Deployment of models in Test / Control framework for tracking b. Build CI/CD pipelines for ML model deployment 9. Integrating AI&ML models with other applications using REST APIs and other connector technologies 10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

The Staff ML Scientist position at Visa offers a unique opportunity to engage in cutting-edge Applied AI research within the realm of data analytics. As a key member of the team, you will play a pivotal role in driving Visa's strategic vision as a leading data-driven company. Your responsibilities will involve formulating complex business problems into technical data challenges, collaborating closely with product stakeholders to ensure the practicality of solutions, and delivering impactful prototypes and production code. You will have the chance to experiment with various datasets, both in-house and third-party, to evaluate their relevance to business objectives. Moreover, your role will encompass building data transformations for structured and unstructured data, exploring and refining modeling and scoring algorithms, and implementing methods for adaptive learning and model validation. Your expertise in automation and predictive analytics will be instrumental in enhancing operational efficiency and performance monitoring. In addition to your technical skills, you will be expected to possess a strong academic background and exceptional software engineering capabilities. A proactive and detail-oriented approach, coupled with excellent collaboration skills, will be essential for success in this role. This is a hybrid position, allowing for a flexible work arrangement that combines remote work and office presence. The expectation is to work from the office 2-3 set days per week, with a general guideline of being in the office at least 50% of the time based on business requirements. Qualifications: - 8 or more years of work experience with a Bachelors Degree or an Advanced Degree - Proficiency in modeling techniques such as logistic regression, Nave Bayes, SVM, decision trees, or neural networks - Ability to program in scripting languages like Perl or Python, and programming languages such as Java, C++, or C# - Familiarity with statistical tools like SAS, R, KNIME, and experience with deep learning frameworks like TensorFlow - Knowledge of Natural Language Processing and working with large datasets using tools such as Hadoop, MapReduce, Pig, or Hive - Publications or presentations in recognized Machine Learning and Data Mining journals/conferences would be advantageous Join Visa as a Staff ML Scientist and contribute to pioneering advancements in Applied AI research that drive innovation and shape the future of data analytics.,

You will be responsible for independently assessing the conceptual framework, methodology, data, and implementation of models. Your role will involve validating models using Statistical and Machine Learning methods. You will be expected to suggest and propose changes in models based on your assessments. Evaluating potential risks associated with model usage and performance, including financial, operational, and reputational risks, will be a key aspect of your duties. Conducting independent performance reviews, back-testing, and benchmarking will also fall under your purview. Ensuring compliance with RBI and other regulatory standards is crucial to this role. Collaboration with the model development team, compliance, audit, and risk teams will be necessary for successful execution of your responsibilities. Additionally, you will need to maintain clear, auditable documentation of validation processes and findings to ensure transparency and accountability.,

As an Actuarial Intern, you will play a key role in supporting various actuarial functions within the organization. Your primary responsibilities will include assisting in the conversion and valuation of different blocks of business, conducting model testing and validation exercises post model conversion, and developing cashflow models for insurance liabilities, investments, and derivatives. To excel in this role, you should have a strong understanding of US Life Products exposure, particularly traditional and/or annuity products. Additionally, you must possess knowledge of pricing, valuation, risk management, model development, model validation, cashflow testing, and ALM. Familiarity with AXIS or similar actuarial projection or valuation software is highly preferred. Your analytical skills will be put to the test as you tackle complex process problems and develop new functionalities and enhancements to existing models. You should be able to effectively manage multiple work assignments, meet time commitments, and communicate effectively both orally and in writing. In addition to your day-to-day responsibilities, you will be expected to perform experience analysis on insurance blocks, prepare income statements and balance sheets for financial models, and conduct movement analysis to monitor and explain changes in the company's capital position. Furthermore, you will support new business activities by evaluating capital requirements for potential acquisitions and reinsurance blocks, as well as provide ad hoc capital analysis and financial projections to support strategic initiatives. This internship opportunity will provide you with valuable hands-on experience in the actuarial field and the opportunity to work on diverse projects that will enhance your skills and knowledge in this specialized area.,

As a Senior Data Scientist in the Global Data Science & Advanced Analytics team at Colgate-Palmolive, your role will involve leading projects within the Analytics Continuum. You will be responsible for conceptualizing and developing machine learning, predictive modeling, simulations, and optimization solutions to address business questions with clear dollar objectives. Your work will have a significant impact on revenue growth management, price elasticity, promotion analytics, and marketing mix modeling. Your responsibilities will include: - Conceptualizing and building predictive modeling solutions to address business use cases - Applying machine learning and AI algorithms to develop scalable solutions for business deployment - Developing end-to-end business solutions from data extraction to statistical modeling - Conducting model validations and continuous improvement of algorithms - Deploying models using Airflow and Docker on Google Cloud Platforms - Leading pricing, promotion, and marketing mix initiatives from scoping to delivery - Studying large datasets to discover trends and patterns - Presenting insights in a clear and interpretable manner to business teams - Developing visualizations using frameworks like Looker, PyDash, Flask, PlotLy, and streamlit - Collaborating closely with business partners across different geographies To qualify for this position, you should have: - A degree in Computer Science, Information Technology, Business Analytics, Data Science, Economics, or Statistics - 5+ years of experience in building statistical models and deriving insights - Proficiency in Python and SQL for coding and statistical modeling - Hands-on experience with statistical models such as linear regression, random forest, SVM, logistic regression, clustering, and Bayesian regression - Knowledge of GitHub, Airflow, and visualization frameworks - Understanding of Google Cloud and related services like Kubernetes and Cloud Build Preferred qualifications include experience with revenue growth management, pricing, marketing mix models, and third-party data. Knowledge of machine learning techniques and Google Cloud products will be advantageous for this role. Colgate-Palmolive is committed to fostering an inclusive environment where diversity is valued, and every individual is treated with respect. As an Equal Opportunity Employer, we encourage applications from candidates with diverse backgrounds and perspectives. If you require accommodation during the application process due to a disability, please complete the request form provided. Join us in building a brighter, healthier future for all.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,