207 Risk Modeling Jobs - Page 2

Job Title: Collection Analytics (Manager) Location: Bangalore/Hyderabad/Noida/Chennai/Gurgaon Job Type: Fulltime Years of Experience- 5-10 years About Straive: Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains. Data Analytics & Al Solutions, Data Al Powered Operations and Education & Learning form the core pillars of the companys long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers. Data Analytics & Al Services: Our Data Solutions business has become critical to our client's success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future- fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them. With a client-base scoping 30 countries worldwide, Straives multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore. Website: https://www.straive.com/ Job Overview: Straive is seeking an experienced Manager - Collection Analytics to join our team. As a remote employee based in the USA, you will work closely with our team to improve our collection strategies and tactics. Roles and Responsibilities: • Develop and implement collection strategies and tactics based on data analysis and insights. - Analyze and interpret data to identify trends and opportunities for improvement. - Collaborate with cross-functional teams to develop and implement new collection processes. Analyze and interpret data to identify trends and opportunities for improvement. - Collaborate with cross-functional teams to develop and implement new collection processes Manage and mentor a team of collection analysts. - Monitor and report on collection metrics, including delinquency rates and recovery rates. - Communicate findings and recommendations to senior leadership. • • • • Risk-Based Collections: Risk scoring is often used to prioritize high-risk accounts for immediate action while allowing more lenient approaches for low-risk borrowers. • The use of advanced analytics can fine-tune this risk scoring process, allowing banks to focus resources where they are most needed. Collection Strategy Optimization: Data analytics driven collections optimization Performance Monitoring & Reporting: • • Advanced analytics tools provide real-time insights into the effectiveness of various collection strategies, teams' performance, and key performance indicators (KPIs) such as recovery rates, time to recovery, and operational efficiency. Dashboards can help in tracking progress and making quick adjustments to tactic. Skills Required: • • Bachelor's or Master's degree in a relevant field. 5-10 years of experience in collection analytics. - Strong analytical skills and experience working with large data sets. • • • • • Experience with statistical analysis and modeling. Strong communication and leadership skills. Ability to work independently and as part of a team. Knowledge of collection regulations and industry best practices. Proficiency in statistical software and programming languages (e.g., Python, R, SQL) and data visualization tools (e.g., Tableau, Power BI).

As a Data Architect in the Utilities domain, you will lead the design and implementation of modern, scalable, and secure enterprise data architectures. Your role involves defining data strategies, creating architecture blueprints, and guiding delivery teams to ensure alignment with business objectives and technical standards. You must possess strong expertise in data modeling, platform architecture, and integration patterns, with the ability to engage both technical and business stakeholders. While your primary focus will be on data architecture, experience in data governance frameworks or utilities analytics will be considered an added advantage. Your responsibilities include defining target-state data architectures and roadmaps aligned with enterprise and utilities industry best practices, conducting current-state assessments of data platforms, integration patterns, and data management processes. You will also be required to develop conceptual, logical, and physical data models for key domains such as customer, billing, asset, and metering. Furthermore, you will establish reference architectures for data ingestion, transformation, storage, and consumption in cloud/hybrid environments, collaborating with engineering teams to ensure designs are implementable, performant, and compliant. Partnering with business teams to translate requirements into scalable, governed data solutions and advising on technology selection for data platforms, integration, and analytics are crucial aspects of your role. In terms of professional and technical skills, you must have a strong background in enterprise data architecture and strategy definition, along with proven experience in the Utilities sector (electricity, gas, or water). Proficiency in conceptual, logical, and physical data modeling, experience with cloud-based data platforms (AWS, Azure, or GCP), data lakes, warehouses, and orchestration tools, as well as an understanding of cloud-native architectures, data lakehouses, and hybrid integration patterns are essential. Additionally, knowledge of data governance frameworks and tools (Collibra, Purview, Unity Catalog), experience in data product design and federated ownership models, familiarity with analytics in the utilities domain such as asset performance and risk modeling, and awareness of SCADA, OMS, PI Historian, and other operational systems are considered good to have skills. The ideal candidate for this role will combine deep Utilities domain knowledge with strong data architecture expertise. This client-facing position involves strategic architecture work and the ability to contribute to delivery in technical projects as required.,

As a Research Engineer at Extreme Event Solutions within Verisk (previously AIR Worldwide), you will have the opportunity to work with cutting-edge technologies and collaborate with a team of skilled professionals in the field of Atmospheric Perils Vulnerability. Your primary responsibility will be to develop models for extreme catastrophic events such as hurricanes, tornadoes, storm surge, and floods, and evaluate building performance under such conditions. You will be tasked with enhancing and supporting the engineering/vulnerability components of Verisk's atmospheric perils portfolio risk analysis models across global regions. This will involve assessing the impact of natural perils on the built environment, including physical damage to buildings, infrastructure, contents, and potential financial losses. Collaboration with a diverse team consisting of structural engineers, meteorologists, statisticians, and risk assessment specialists will be essential in this role. The successful candidate for this position should possess a Ph.D. in Civil Engineering with a focus on Structural Engineering, along with experience in performance-based design, probabilistic risk assessment, and reliability theory. Proficiency in programming languages such as C/C++, Python, and productivity software like R, MATLAB, and Microsoft Office is required. Additionally, strong communication, organizational, and documentation skills are essential for presenting research findings to both internal stakeholders and external clients. Your day-to-day responsibilities will include data acquisition and analysis to understand building vulnerability, developing vulnerability functions for building components exposed to various hazards, implementing research into Verisk's risk analysis models, and utilizing GIS tools for data visualization. You will also be involved in real-time building damage assessments during natural catastrophes and presenting your work at internal and external meetings. Verisk values inclusivity, diversity, and workplace culture, providing employees with opportunities for professional growth and development. By joining Verisk, you will be part of a global team dedicated to translating data into innovative solutions for a better tomorrow. If you are a motivated individual with a passion for problem-solving and a desire to excel in the field of civil engineering and risk assessment, this role offers a unique opportunity to make a meaningful impact. For more information about careers at Verisk, visit our website at https://www.verisk.com/company/careers/.,

As a Data Scientist with a proven track record in Predictive analytics, your main responsibilities will include building and modeling scorecards, developing analytical models to assess risk profiles of customers, identifying cross-sell opportunities, and fraud control for both new and existing customers. You will be responsible for developing and deploying various scorecards and models for credit risk and retail asset products within specified timelines, ensuring alignment with the Bank's strategies for maximum efficiencies. Your role will also involve estimating the probability of default from the scorecards, monitoring deviations from expected default rates, identifying opportunities for business growth, and providing risk alerts to control NPAs. You will be expected to formulate data cuts and strategies to assess credit risk, provide feedback to stakeholders for model improvement, develop novel approaches in Risk modeling, and adopt the latest trends in fintech companies. Additionally, you will work on the automation of scorecards in the Analytics domain and explore untapped data sources within the Bank's ecosystem to meet business objectives. You will be encouraged to innovate, evolve processes, and make significant changes to save time, energy, and money while handling any other assignments as per the organization's needs. To qualify for this role, you should have an educational background in MCA/MTech/MSc Statistics or Economics/BTech/MBA or equivalent in Computer Science/Statistics, with a strong inclination towards machine learning algorithms. Key skills required include excellent problem-solving capabilities, strong fundamentals in computer science, technical and analytical skills, hands-on experience in data wrangling, feature engineering, and deploying scalable machine learning algorithms. Moreover, you should possess strong written and verbal communication skills and stay updated on current trends in the machine learning/analytics field. Ideally, you should have at least 2+ years of experience in analytics, predictive modeling, or machine learning, with proficiency in Python/R for building and deploying scalable analytics models. Exposure to the banking sector would be advantageous for this role.,

The purpose of your role is to define, implement, and oversee the credit strategy and risk framework for the Loan Against Property (LAP) business with a ticket size of up to 75 Lacs. You will be responsible for ensuring sustainable portfolio growth while maintaining an optimal risk-return balance. Your duties will include policy formulation, governance, portfolio oversight, and enabling business teams to achieve disbursement and profitability targets with strong asset quality. Your key responsibilities will involve: 1. Credit Strategy & Policy: Developing and updating credit policies, underwriting guidelines, and scorecards tailored for LAP. Aligning credit risk frameworks with RBI/NBFC regulatory guidelines and internal risk appetite. Defining risk-based pricing models and establishing TAT benchmarks for approval processes. 2. Underwriting & Portfolio Management: Leading national underwriting operations, ensuring robust borrower and collateral evaluation. Monitoring portfolio vintage-wise delinquencies, early warning indicators, and NPA trends, and initiating corrective measures. Approving high-value or exception cases beyond delegated authority levels of zonal/regional credit managers. 3. Operational Excellence: Standardizing credit approval workflows across branches, hubs, and digital channels. Collaborating with Technology & Operations to digitize credit journeys, integrate LOS/LMS systems, and improve risk analytics. 4. Business Collaboration: Partnering with Sales & Product teams to design profitable customer segments, sourcing strategies, and new product variants. Providing policy refreshers, credit training, and guidance to Sales teams, DSAs, and regional credit units. 5. Governance & Compliance: Ensuring zero major audit observations and adherence to internal/external compliance requirements. Presenting portfolio health reports to senior leadership, credit committees, and risk boards regularly. 6. Team Leadership: Leading & mentoring regional/zonal credit heads and credit analysts, driving productivity, quality, and succession planning. Fostering a high-performance, compliance-oriented culture with clear accountability metrics. You should possess the following know-how skills: - Domain Knowledge: Deep expertise in retail secured lending (LAP, MSME, Home Loans). Strong understanding of property valuation, legal scrutiny, and surrogate income assessment for self-employed borrowers. Regulatory knowledge of RBI/NBFC norms, KYC/AML guidelines. - Technical Skills: Credit MIS & portfolio analytics, delinquency dashboards, and scorecards. Familiarity with LOS/LMS systems and digital underwriting platforms. Basic knowledge of risk modeling, policy automation, and digitization initiatives. - Leadership & Behavioral Competencies: Strategic decision-making and risk appetite calibration. Ability to balance business growth and portfolio quality. Strong stakeholder management & cross-functional collaboration. Proven team leadership, mentoring, and succession planning skills. You are required to have: - Education & Experience: MBA (Finance/Risk), CA, or equivalent qualification. 10-15 years of credit & risk management experience, with at least 5 years in a leadership role in LAP/secured lending.,

The Credit Strategy team at Navi is responsible for developing and optimizing underwriting strategies across key lending products. The team focuses on key underwriting metrics, asset quality indicators, and portfolio monitoring to ensure that credit decisions align with business objectives and risk tolerance. Continually enhancing underwriting quality and portfolio health is a priority to support sustainable growth. As a Model Strategist on the Credit Strategy team at Navi, we are seeking a highly curious and structured thinker. This role is designed for individuals who deeply understand models and aim to influence their usage and purpose rather than solely focusing on building them. In this position, you will be at the intersection of product, data science, and business, guiding model selection, challenging performance, and shaping solver logic to maximize disbursal while maintaining control over credit costs. This unique role combines system-level thinking with significant business impact, making it ideal for data scientists or quantitative analysts looking to contribute to high-stakes decision-making. Key Responsibilities: - Evaluate and challenge model performance across risk segments, funnel stages, and product variants - Drive model selection logic, deciding when and how to use specific models and blending multiple signals - Brainstorm on modeling techniques, data handling, and exclusions to enhance model performance - Collaborate with Data Science to recommend improved feature sets, inputs, and architecture hypotheses - Own solver logic and trade-off frameworks, such as approval rate versus ACL - Lead test-and-learn initiatives in underwriting experiments - Influence end-to-end underwriting strategy with a precision-first approach Qualifications: - Strong background in data science, credit analytics, or risk modeling (3+ years) - Hands-on experience with building and evaluating ML models, especially in lending or financial domains - Deep understanding and practical experience with modern ML and deep learning techniques - Ability to command respect from data science teams through technical credibility and insight - Curiosity about how models drive business outcomes, emphasizing precision over accuracy - Strong problem-solving skills and structured thinking - Masters or Bachelors degree in Computer Science, Electrical Engineering, Mathematics, Economics, or a related quantitative discipline - PhD in Data Science, ML, or Statistics from a reputable institution is a strong plus - Bonus: Exposure to lending, fintech, credit cards, BNPL, startups, or consulting Join Navi and be part of shaping the future of financial services for a billion Indians. Our tech-first solutions prioritize simplicity, accessibility, and affordability, covering a range of products such as Personal & Home Loans, UPI, Insurance, Mutual Funds, and Gold. Founded by Sachin Bansal & Ankit Agarwal in 2018, Navi is a rapidly growing financial services organization with a strong customer-first approach. Our Culture: At Navi, we value ambition, perseverance, self-awareness, ownership, and integrity. We seek individuals who dream big, innovate, and deliver real value to customers. If you are driven by challenges and aspire to make a difference, join us in a dynamic team that builds innovative solutions and uplifts each other to achieve excellence. Why You'll Thrive at Navi: - You're impact-driven: Take ownership, build boldly, and strive to make a real difference - You strive for excellence: Maintain focus, precision, and a passion for quality - You embrace change: Adapt quickly, prioritize the customer, and move fast to meet evolving needs,

Formulation of Credit Policy for assigned products Review amendment proposal to credit policies Monitor effective implementation of credit policies Review and Analysis of historical loan data to understand the pattern from delinquency point of view Apply statistical tool to analyze the pattern and come with detailed assessment Review and Prepare risk dashboard for management which shows all important risk parameters Customer, vendor, competition visits & Market analysis Develop rating model/scorecard for various retail and corporate loans based on historical data Testing of scorecard/model on a regular basis and update Coordinate with various stakeholder for the rating model implementation Prepare and maintain database of loan products from risk assessment point of view Ensure data is correctly captured in the system and coordinate with different teams to fix the issue. Review and Preparation of regular credit risk reports for Board meeting and other management committee meeting consumption Regulatory, Audit reporting interested candidate can share their resume on adarsh.pandey@utkarsh.bank.

Position Purpose :- Lead the Card Risk Analytics team which supports the credit cards business in the following areas: Modelling, Acquisition, Credit Risk Management & Fraud Risk Position Responsibilities :- Drive next generation of analytical solutions in Credit Cards :- - Revamp Acquisition Rules to drive profitable and risk-adjusted growth - Enhance Card Limit assignment framework - Identify cohorts and segments to drive acquisition volume for various sourcing channels and key co-brand partners - Drive Portfolio interventions both Positive and Negative – to identify enhancement opportunities (offer base enhancement, line/loan amount assignment) - Enhance Fraud Risk Management by enhancing Rule efficacy, developing Fraud Models Lead Risk, Collection and Marketing model development and monitoring of the models for Credit Cards portfolio Drive business efficiencies :- - Focus on Cross-Sell: Develop targeted pre-approved bases for Cross-sell of Loans/Cards to existing customers in the Bank - Develop portfolio segmentation to enhance customer engagement, encourage profitable spend and reduce Credit losses through sharper interventions - Work towards achieving Infrastructure enhancements that would facilitate advanced analytics and data science Independently manage and lead analytics projects and manage relationship with stakeholders Engage with internal stakeholders – such as Business, Risk, Collection for generating ideas of analytics projects and answer / explain challenges in respective areas Engage with external stakeholders – Partners, Credit Bureaus, Fintechs etc. Manage a large team of 25+ people

You will be a part of KPMG India, a professional services firm affiliated with KPMG International Limited, with offices in various cities across the country. Your role will involve working on Model Validation and Model Development related to Market Risk. You should have proven experience in market risk, risk modeling, or model validation, and be familiar with assessing the conceptual soundness and methodology of models such as Value at Risk, Counterparty Risk Exposure models, Pricing of derivatives, and Stress Test Models. Your responsibilities will include producing high-quality model validation reports, understanding regulations and guidelines for model risk management, and assessing the appropriateness of input data, model assumptions, and parameters. You will also be required to review outcomes, perform benchmark analysis, and identify model limitations. Proficiency in programming languages like SAS, R, Python, and a fair understanding of SQL, along with proficiency in Microsoft Word, Excel, Visio, PowerPoint, and Latex will be advantageous. As part of KPMG India, you will have the opportunity to work with national and international clients across various sectors, providing industry-focused and technology-enabled services based on global and local industry knowledge and experience of the Indian business environment.,

Role & responsibilities Implement Credit policy logic in Credit/Business rule engine and monitoring Develop logic and conduct testing of implemented logic Responsible for implementing credit policy in coordination with risk ,IT , product and Business Support in implementation of projects and product development to mitigate credit risk in the organization Prepare/Analyse/maintain credit risk models (scenario testing) in line with requirements of organization. Prepare risk reports on a regular basis. Identifying and analysing potential credit risk areas based on the data provided and recommending action plans Preferred candidate profile 1-4 years experience (preferably in MFI/FI/Bank/working in Credit risk domain) Engineering/ MBA(Finance) Proficient in MS-Office (Excel, PowerPoint and Word) Strong analytical skills. Knowledge of analytical tool (preferably R/Python/SAS)- python must Strong English verbal and writing skills understanding of MFI/FI/Bank business environment is plus Regards, Sandipa 7980475998

About The Role : In Scope of Position based Promotions (INTERNAL only) Job Title- IB Business Information Records Officer (BIRO) Location- Mumbai, India Corporate Title - VP Role Description Group Strategic Analytics: Analytics and technology are seen as central to all the main units of the bank, including Investment Bank, Corporate Bank and to Risk and Control functions. The Strategic Analytics team combines expertise in quantitative analytics, modelling, pricing and risk management with deep understanding of system architecture and programming. The primary output is a scalable and flexible Front Office pricing and risk management system with consistent interface to both the Middle Office and Back Office. The consistency in analytics and the technology platform ensures that no arbitrage can exist between various parts of the Bank as well as rational allocation of constrained resources, including risk budget, balance sheet, funding, and capital. What well offer you 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Accident and Term life Insurance Your key responsibilities Treasury Strat's The candidate is required to work in collaboration with London/New York/Frankfurt team on various quantitative and regulatory driven projects. Candidate is required to understand the business problem, gather information required for the implementation and provide an end-to-end optimized solution on a scalable platform. Implementation of the project needs to be done in Python and C++ programming language. Candidate should possess a very good English communication skill in order to coordinate and communicate their work effectively with various stakeholders spread across globe. Role Responsibilities Development of complex processes, framework or risk analysis as well as improvements Implement, enhance and maintain existing framework to measure market risks across the bank Understand and decipher business problem to convert into manageable smaller problem statements Coordinate and gather information from various stakeholders for deeper understanding of the business Design an automated solution which is optimized and scalable Develop and design tables and databases required for the storage of the data Develop applications/libraries for the implementation of the solution Remediation of regulatory as well as external and internal findings against the MR HS models in line with the assigned tasks Constant awareness and understanding of the key market risks taken by the business areas and communication to senior management and with ex External stakeholders, challenge the business within assigned areas when required Quality assurance (e.g. 4 eyes principle reviews) Your skills and experience Competencies Programming Skills At least 4 years experience in Python/C++ programming Good knowledge of OOPs programming concepts ( Class, Pointers, Data structure stacks, queue) Experience in pulling data from various Market data sources. Independent handling and mitigating methodological or process weaknesses identified by regulators, auditors and internal model validation team Strong communication skills and presentation ability with attention to detail Good problem solving instincts and strong analytical skills Personal characteristics Ability to work independently as well as flexibly within intra or inter-departmental groups. Continuous advancement of own skills and knowledge Can-Do attitude & Able to cope well under pressure and tight deadlines. Education/ Qualifications: Strong educational background in Engineering/Science, Economics, Statistics or other numerate discipline preferably from good colleges in India e.g. IIT, NIT, ISI etc. Good knowledge of financial instruments and markets across all asset classes Knowledge of financial pricing models, risk models would be desirable Experience with applied econometrics (Hypothesis testing, PCA, Linear/Non-Linear Regression etc) will be a plus Certification courses like CFA/FRM/CQ How well support you

About The Role : Job TitleQuant Analyst, AVP LocationMumbai, India Role Description Group Strategic Analytics: Analytics and technology are seen as central to all the main units of the bank, including Investment Bank, Corporate Bank and to Risk and Control functions. The Strategic Analytics team combines expertise in quantitative analytics, modelling, pricing and risk management with deep understanding of system architecture and programming. The primary output is a scalable and flexible Front Office pricing and risk management system with consistent interface to both the Middle Office and Back Office. The consistency in analytics and the technology platform ensures that no arbitrage can exist between various parts of the Bank as well as rational allocation of constrained resources, including risk budget, balance sheet, funding, and capital. What well offer you 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Accident and Term life Insurance Your key responsibilities Treasury Strat's The candidate is required to work in collaboration with London/New York/Frankfurt team on various quantitative and regulatory driven projects. Candidate is required to understand the business problem, gather information required for the implementation and provide an end-to-end optimized solution on a scalable platform. Implementation of the project needs to be done in Python and C++ programming language. Candidate should possess a very good English communication skill in order to coordinate and communicate their work effectively with various stakeholders spread across globe. Role Responsibilities Development of complex processes, framework or risk analysis as well as improvements Implement, enhance and maintain existing framework to measure market risks across the bank Understand and decipher business problem to convert into manageable smaller problem statements Coordinate and gather information from various stakeholders for deeper understanding of the business Design an automated solution which is optimized and scalable Develop and design tables and databases required for the storage of the data Develop applications/libraries for the implementation of the solution Remediation of regulatory as well as external and internal findings against the MR HS models in line with the assigned tasks Constant awareness and understanding of the key market risks taken by the business areas and communication to senior management and with ex External stakeholders, challenge the business within assigned areas when required Quality assurance (e.g. 4 eyes principle reviews) Your skills and experience Competencies Programming Skills At least 4 years experience in Python/C++ programming Good knowledge of OOPs programming concepts ( Class, Pointers, Data structure stacks, queue) Experience in pulling data from various Market data sources. Independent handling and mitigating methodological or process weaknesses identified by regulators, auditors and internal model validation team Strong communication skills and presentation ability with attention to detail Good problem solving instincts and strong analytical skills Personal characteristics Ability to work independently as well as flexibly within intra or inter-departmental groups. Continuous advancement of own skills and knowledge Can-Do attitude & Able to cope well under pressure and tight deadlines. Education/ Qualifications: Strong educational background in Engineering/Science, Economics, Statistics or other numerate discipline preferably from good colleges in India e.g. IIT, NIT, ISI etc. Good knowledge of financial instruments and markets across all asset classes Knowledge of financial pricing models, risk models would be desirable Experience with applied econometrics (Hypothesis testing, PCA, Linear/Non-Linear Regression etc) will be a plus Certification courses like CFA/FRM/CQ How well support you

Enterprise Portfolio Researcher We are looking for a motivated Quantitative Risk Modeler with 1- 3 years of experience to join our team. This role focuses on developing and maintaining multi-asset class analytics frameworks to the Firmwide portfolio of teams and senior management decision-making. If you have a passion for quantitative finance, risk modeling, and applied statistics, this is an excellent opportunity to grow your career in a dynamic and collaborative environment. Principal Responsibilities: Development of multi-asset class analytics across all MLP strategies, supporting the Office of the CIO across Enterprise-wide initiatives. This includes working on the centralized performance evaluation framework at MLP, improvements on VaR and Stress methodologies, as well as implementing centralized back-testing and model performance frameworks. Contributions to the development of multi-asset class content generation, as well as centralized visualization tools for the platform used by senior management. Ownership in developing a quantitative framework for identifying, measuring, managing, and reporting multi-asset class analytics across the platform PM performance measurement and analytics to help inform management decisions. Ownership of a multi-asset class stress-testing framework, including insights into key risk drivers to action management decisions. Capital utilization and allocation models across portfolio manager teams. Cost of liquidation measurement and management, as well as associated returns relative to constrained resources. Post initial model development work, coordinate with relevant Technology departments to ensure changes are deployed into to production. Qualifications: The candidate should have a degree in a quantitative field such as statistics, mathematics, computer science or financial engineering. Strong programming skills, prior experience with Python (Polars and/or Pandas). Proficiency in at least a compiled and statically typed language is a plus. Knowledge of mathematical and statistical analytics tools: estimation of linear models, dimensionality reduction techniques e.g. Equity Factor Models, Principal Component Analysis, and performance analytics (e.g., Sharpe ratios, drawdowns). Sense of responsibility and integrity. Intellectual curiosity and entrepreneurial mindset. Willingness to work and have fun in the process. Good presentation and communication skills, experience in either preparing or participating presentation for senior management-style meetings.

You are a highly skilled Quantitative Developer / Algorithmic Developer with 3 to 7 years of experience, seeking to join a team focused on building advanced, production-grade crypto trading systems. Your role involves developing and optimizing algorithmic trading strategies, designing robust infrastructure, integrating with exchanges, and converting research ideas into actionable trading logic. You should excel at strategy development, high-performance Python programming, and system design, with a deep interest in cryptocurrency markets. Your key responsibilities will include designing, building, and deploying crypto trading strategies across spot, futures, and derivatives. You will translate strategy logic into efficient Python code, work on data ingestion and pattern recognition, integrate machine learning models, interface with exchange APIs, manage data storage, optimize for latency and robustness, and develop internal tools for monitoring and strategy deployment. To excel in this role, you must have strong hands-on programming experience in Python, solid understanding of algorithmic trading systems, proficiency in PostgreSQL, Redis, and FastAPI, familiarity with crypto exchange APIs, and quantitative strategy concepts. You should be detail-oriented, have prior experience with strategy development, and possess a deep curiosity about crypto markets. Preferred qualifications include experience in systematic trading, knowledge of pattern detection systems, exposure to machine learning models applied to financial data, and an understanding of portfolio optimization and risk modeling. If you are passionate about crypto markets and want to contribute to the next generation of intelligent trading systems, this role offers an exciting opportunity to collaborate with quant researchers, infra engineers, and traders in shaping the future of crypto trading.,

You are a highly accomplished and strategic professional sought after to join the Financial Risk Management (FRM) team within the Risk Advisory service line at KPMG India. Your deep expertise in financial risk, regulatory compliance, and advisory services, particularly in the banking and financial services sector, will be invaluable in this role. As a Director in the FRM team, you will lead and manage large-scale risk transformation programs focusing on credit risk, market risk, and regulatory compliance. Your responsibilities will include performing Basel III Reforms divergence analysis, optimizing ICAAP processes, automating regulatory reports, and leading regulatory change initiatives such as Basel III/IV, ICAAP, RRP, APRA, PRA, FINMA, and RBI compliance. Additionally, you will support quarterly capital reporting for APRA and drive client engagement from proposal development to delivery. To excel in this role, you should possess 12-15+ years of experience in financial risk management, either in consulting or the BFSI sector, along with a strong understanding of regulatory frameworks. You must have proven experience in managing P&L, delivering on revenue and margin targets, and exceptional leadership, communication, and stakeholder management skills. Analytical and quantitative skills, including risk modeling and scenario analysis, are essential, as well as excellent communication and presentation skills for CXO-level interactions. Your qualifications should include CA, MBA (Finance), CFA, FRM, or equivalent professional certifications, along with a strong academic background in finance, economics, statistics, or related fields. Additional certifications in risk management or data analytics would be considered a plus. KPMG India is an equal opportunity employer where professionals like you can leverage the global network of firms, stay informed about local laws, regulations, markets, and competition, and contribute to the growth and success of the organization.,

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.

Job Responsibilities: Data Collection and Preparation: Collaborate with cross-functional teams, including domain experts, to collect and preprocess relevant data from multiple sources (e.g., healthcare records, financial transactions). Conduct thorough data analysis, cleaning, and feature engineering to transform raw data into usable formats for model development. Ensure data privacy and security compliance when handling sensitive data. Machine Learning Model Development: Design, build, and implement machine learning models tailored to solve specific business challenges Select appropriate datasets and data representation methods for various projects (e.g., time-series data, structured/unstructured data). Experiment with and optimize algorithms (e.g., supervised learning, unsupervised learning, anomaly detection) to improve model accuracy and efficiency. Perform statistical analysis, test different hypotheses, and fine-tune models using test results. Model Optimization and Evaluation: Evaluate model performance using various metrics (accuracy, precision, recall, F1 score, etc.) and apply techniques such as cross-validation, hyperparameter tuning Continuously improve models based on feedback, new data, and evolving business requirements. Ensure models can scale effectively in production environments. Model Deployment and Monitoring: Deploy machine learning models into production using cloud services (AWS, GCP, Azure) or containerized environments (Docker, Kubernetes). Oversee and monitor the performance of models in real-time, ensuring they provide accurate and actionable insights. Implement model retraining and continuous learning processes to maintain performance over time. Research and Innovation: Stay current with the latest developments in machine learning, AI, and relevant technologies by actively researching and experimenting with new algorithms, models, and techniques. Propose and integrate novel approaches into existing workflows to improve model accuracy, efficiency, and scalability. Required Qualifications: Technical Skills: Programming Languages : Proficiency in Python, Java, or R, with strong expertise in Python for machine learning tasks. Machine Learning Frameworks : Familiarity with TensorFlow, PyTorch, Keras, and scikit-learn for developing and optimizing models. Mathematics & Statistics : Strong foundation in linear algebra, calculus, probability, and statistics to understand and apply machine learning algorithms effectively. Big Data Technologies : Experience working with tools like Hadoop, Apache Spark for handling large datasets. Cloud Computing : Hands-on experience with cloud platforms such as AWS, GCP, or Azure for deploying and maintaining machine learning models. Version Control & Deployment : Proficient with version control tools like Git and experience in CI/CD pipelines for model deployment. Domain-Specific Knowledge (Desired): Healthcare/Medical Data : Understanding of medical datasets (e.g., patient records, diagnostic imaging) and how to build models for healthcare applications (e.g., predicting neurological disorders). Financial Data/Fraud Detection : Experience with financial transaction data and building systems for detecting fraudulent activity and financial anomalies (e.g., Anti-Money Laundering models). Soft Skills: Problem-Solving : Strong analytical and problem-solving skills, with the ability to approach challenges in creative and innovative ways. Communication : Excellent written and verbal communication skills, with the ability to explain complex machine learning concepts to non-technical stakeholders. Team Collaboration : Ability to work collaboratively in an interdisciplinary team, sharing knowledge and working towards common goals.

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

The Risk Testing Group (RTG) at Goldman Sachs is a diverse team of quantitative and financial experts located in Bangalore, Hyderabad, Mumbai, New York, Dallas, and Salt Lake City. RTG's main focus is on the independent oversight of all financial and non-financial risks to ensure compliance with both regulatory requirements and internal standards. The group's core responsibility involves conducting independent reviews of models, data, processes, controls, and systems related to various risk categories such as Credit, Market, Operational, and Liquidity. As part of the Risk division, you will be directly involved in managing credit, market, and operational risk, as well as model risk, independent liquidity risk, and insurance across the firm. The RTG team is currently seeking an Analyst who will be engaged in challenging projects aimed at analyzing risk management practices comprehensively. This role will require collaboration with stakeholders within the company and regulatory bodies across different regions, providing exposure to a wide array of financial products, risk management tools, quantification techniques, and diverse technological platforms. Your responsibilities will include developing a deep understanding of the firm's risk management framework, models, methodology, and processes. You will conduct independent reviews of key regulatory and internal initiatives, presenting your findings through formal reports. Additionally, you will be responsible for validating the firm's qualitative models by assessing conceptual soundness, methodology, and implementation. Building and maintaining effective relationships with stakeholders and presenting results to senior management committees and regulators will also be a key aspect of your role. Basic qualifications for this position include a minimum of a bachelor's degree, with a preference for candidates holding a Master's degree in a quantitative discipline. Qualified Chartered Accountants (CAs) are also encouraged to apply, while professional certifications such as CFA, FRM, or equivalent are advantageous. The ideal candidate should possess expertise in qualitative and quantitative risk management, particularly in credit, market, liquidity, or operational risk. Strong programming skills, especially in an object-oriented programming language like C++ or Python, are essential. The ability to handle multiple tasks effectively, take initiative, work towards challenging goals, and collaborate with team members are critical competencies for success in this role. At Goldman Sachs, we are dedicated to supporting our clients, shareholders, and the communities we serve by leveraging the skills and ideas of our talented employees. Founded in 1869, we are a prominent global investment banking, securities, and investment management firm with a commitment to diversity and inclusion. We offer numerous opportunities for professional growth and personal development through training programs, networks, benefits, and wellness initiatives. Goldman Sachs is an equal opportunity employer and is committed to providing reasonable accommodations for candidates with special needs or disabilities during the recruitment process. To learn more about our culture, benefits, and career opportunities, visit GS.com/careers.,

Exp in SAS, SQL and large amounts of data US Stakeholder exp Exp of acquisition/account management credit risk models, transactional fraud models, marketing models, collections models, finance models, loss models, Loss forecasting (PD/LGD/EAD/CECL) Required Candidate profile SAS SQL Python Credit risk Credit Card Statistical Modelling Predictive Modelling

Salary : 30 to 45 LPA Exp: 6 to 10 years Location :Hyderabad (Hybrid) Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

You will be acting as the internal safety and risk subject matter expert within the CoE, supporting strategic initiatives and solution development. Your responsibilities will include collaborating with the Engineering team to guide feature design, ensuring alignment with safety/risk standards, and validating product performance from a practitioners" perspective. Additionally, you will provide feedback and validation on user workflows, risk modeling logic, and analytics tied to SIF prevention and SMS best practices. To excel in this role, you should have at least 5 years of experience in safety, EHS, loss control, enterprise risk management, or industrial hygiene. A deep understanding and familiarity with EHS/safety software platforms or direct experience supporting such system implementations are essential. You should possess a strong working knowledge of SIF prevention strategies, risk modeling, and root cause analysis. Experience working across departments in a matrixed or consulting environment is highly desirable. In terms of skills and tools, proficiency with data tools such as Power BI, Excel, and Tableau is required. You should be comfortable working with structured safety and risk data. Strong communication skills are necessary to engage both technical and non-technical audiences effectively. Your ability to translate regulatory and operational requirements into software and service solutions will be crucial. Exposure to Agile product development, SaaS environments, or cross-functional collaboration with engineering/development teams is considered a bonus. Overall, this role requires expertise in EHS applications, Tableau, data analysis, Excel, Power BI, industrial hygiene, root cause analysis, SaaS, loss control, enterprise risk management, risk modeling, agile product development, SIF, as well as safety and risk management.,

Responsibilities: Develop and optimize fixed-income analytics in C++ and integrate with existing client systems. Work on curve construction, bond pricing, and risk management analytics. Collaborate with quants and software engineers to enhance the performance of analytical models. Implement robust software engineering practices to ensure model reliability and scalability. Conduct thorough unit testing and performance benchmarking. Skills & Qualifications: At least 7-8 years of experience in building various models in the financial services space Strong proficiency in C++, including multithreading and performance optimization. In-depth understanding of fixed-income securities, term structure models, and derivatives pricing. Experience with financial libraries such as QuantLib or proprietary quant frameworks. Exposure to cloud-based and high-performance computing environments. Strong knowledge of risk analytics and fixed-income portfolio management. Key Responsibilities Develop and implement Treasury Futures and Options on Treasury Futures Models in BondCalc. Expand and enhance test suites to validate the implementation. Collaborate with Quants and Quant Developers to modernize analytics infrastructure for bonds. Ensure compliance with industry-standard style guidelines for coding and model implementation. Conduct model validation, risk calculations, and performance tuning. Required Skillset Strong expertise in C++ development, particularly in quantitative analysis and financial modeling. Experience with Python, TypeScript, and SQL for data processing and analytics. Deep knowledge of fixed income analytics, risk modeling, and derivative pricing. Hands-on experience with server-side infrastructure and database components. Ability to work in a trading desk or asset management environment. Ensure compliance with industry standards and testing protocols. Preferred Qualifications Experience working in investment banking or asset management environments. Familiarity with quant libraries and financial engineering concepts. Proven track record of delivering large-scale quantitative development projects.

This is an Internal document. Role- Credit Risk and Policy Manager Job Purpose: To design, implement, and manage credit risk policies and strategies that ensure healthy portfolio performance, mitigate default risk, and support business growth. This role involves credit underwriting frameworks, portfolio analytics, risk appetite definition, and policy governance. Key Responsibilities: Credit Policy & Frameworks: Develop and regularly update credit risk policies, product programs, and underwriting guidelines for various customer segments (retail, SME, corporate, etc.). Define risk acceptance criteria based on internal data and market intelligence. Collaborate with business, operations, legal, and compliance teams to implement and operationalize credit policies. Risk Assessment & Monitoring: Analyze credit risk across new and existing products and segments. Establish early warning signals (EWS) and monitoring frameworks to track portfolio health. Design scorecards, segmentations, and risk models in collaboration with analytics and data science teams. Portfolio Management: Track key credit metrics such as delinquency, NPAs, write-offs, LGDs, and PDs. Recommend changes in credit strategies or policy thresholds based on portfolio trends. Benchmark internal performance with industry standards. Regulatory & Compliance: Ensure policies align with regulatory guidelines (RBI, Basel norms, etc.). Prepare risk-related reports and documentation for audits and regulatory reviews. Stakeholder Management: Work closely with credit, collections, risk analytics, legal, and technology teams. This is an Internal document. Provide training and guidance on credit policies to credit and sales teams. Qualifications & Experience: Bachelors degree in Finance, Economics, Statistics, or related field (MBA/CA/CFA preferred). 410 years of experience in credit risk, policy formulation, or credit underwriting (depending on seniority). Strong understanding of lending products (personal loans, SME, mortgages, BNPL, etc.). Experience with data analysis, credit scoring, and risk modeling is a plus. Skills & Competencies: Analytical thinking with sound risk judgment. Strong knowledge of credit lifecycle and portfolio management. Proficient in Excel, SQL, and/or data visualization tools (Power BI/Tableau). Excellent communication and stakeholder management skills.