12 Ecl Jobs

Model Monitoring/Model Validation EXL (NASDAQ:EXLS) is a leading operations management and analytics company that helps businesses enhance growth and profitability in the face of relentless competition and continuous disruption. Using our proprietary, award-winning methodologies, that integrate advanced analytics, data management, digital, BPO, consulting, industry best practices and technology platforms, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation and logistics industries. Headquartered in New York, New York, EXL has more than 30,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), Latin America, Australia and South Africa. EXL Analytics provides data-driven, action-oriented solutions to business problems through statistical data mining, cutting edge analytics techniques and a consultative approach. Leveraging proprietary methodology and best-of-breed technology, EXL Analytics takes an industry-specific approach to transform our clients decision making and embed analytics more deeply into their business processes. Our global footprint of nearly 2,000 data scientists and analysts assist client organizations with complex risk minimization methods, advanced marketing, pricing and CRM strategies, internal cost analysis, and cost and resource optimization within the organization. EXL Analytics serves the insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation and logistics industries. Please visit www.exlservice.com for more information about EXL Analytics. Home EXL Service is a global analytics and digital solutions company serving industries including insurance, healthcare, banking and financial services, media, retail, and others Role Details : We are seeking a strong credit risk model professional with experience in model monitoring, validation, implementation and maintenance of regulatory models. Responsibilities: Helping with various aspects of model validation Perform all required tests (e.g. model performance, sensitivity, back-testing, etc.) Interact with model governance team on model build and model monitoring Work closely with cross functional teams including business stakeholders, model validation and governance teams Deliver high quality client services, including model documentations, within expected timeframes Requirements : Minimum 2+ years of experience in executing end to end monitoring/validation/production/implementation of risk model validation/monitoring understanding with respect to marketing/general analytics problems Managing assigned projects in a timely manner, ensuring accuracy and that deliverables are met. Training, coaching and development of team members Qualifications: Previous experience (2+ years) in analytics, preferably in BFSI Good knowledge in General Analytics, Fraud Analytics Past experience in problem solving roles, strategic initiatives Good problem-solving skills

Salary: 15 to 30 LPA Exp: 3 to 7 years Location: PAN India Notice: Immediate only..!! Key Skills: SQL, Power BI, Credit Risk, risk analytics, MIS, risk reporting Roles and Responsibilities Extract, manipulate, and analyze large datasets from various sources such as Hive, SQL databases, and ETL processes. Develop and maintain dashboards using Tableau to provide insights on banking performance, market trends, and customer behavior. Collaborate with cross-functional teams to identify key performance indicators (KPIs) and develop data visualizations to drive business decisions. Desired Candidate Profile 3-8 years of experience in Data Analytics or related field with expertise in Banking Analytics, Credit risk . Strong proficiency in tools like SQL, Advance SQL knowledge preferred. Experience working with big data technologies like Hadoop ecosystem (Hive), Spark; familiarity with Python programming language required.

About the Role: Senior Data Analyst Core Responsibilities: The successful candidate will be responsible for supporting business function teams to analyze and execute ideas and drive initiatives designed to achieve business growth, along with loss mitigation goals. The core responsibilities will include. Orchestrate end-to-end credit-risk analytics: extract bureau + alt-data features, run feature-selection, train models, and then translate those into limit, tenor and approval rules recommendations. Managing Credit risk framework by creating probabilistic loss forecasts using vintagecurve time series progressions, survival-hazard models and Markov chain / Vasicek ECL models. Identification of business opportunities by decomposing acquisition funnels, isolating the reasons for true causal lift through frameworks like T-learner, tree-based segmentation etc. Shape next-gen underwriting stack by crafting strategies for -- score cut-offs, tenor reshaping, limit-increase logic, use of alternate credit data points -- and quantify their P&L impact before rollout Simulate what-if” scenarios and recommend cohort-specific pricing/risk shifts own the data-science storyline in CXOs and board forums, securing green-lights (or kill calls) for high-stakes experiments. Preference and Experience: Working experience as a Data Analyst or Business Data Analyst. Fluency in bureau datapoints, functional knowledge of consumer lending processes (risk/profit economics, RBI digital-lending rules, alternate credit datapoints) Strong command of Python and SQL for large-scale data analysis, plus hands-on experience with any BI dashboards. Knowledge of statistics and experience of using statistical models for analyzing datasets. Able to design experiments, interpret results, and prepare recommendations for C-suite, credit risk teams. Educational Requirements: MBA and a Degree in Statistics, Physics, Applied Mathematics, Operations Research, Econometrics, Engineering, or another quantitative discipline.

Job Overview & Responsibilities: The individual will be part of Financial reporting team specifically leading accounting for Wholesale (WS) segment. Candidate would be primarily responsible for review o f: Responsible for financial reporting for a business segment including EIR, TDS, ECL, NPAs etc Preparing high quality deliverables with analysis for a business segment Ensuring reconciliation between Accounting and LMS systems Continuous interaction with senior management of business segment to have a full overview and understanding of business including specific loans Data analysis Yield analyses, Loan book analysis, Loan book movement, Interest and processing fee, Credit Cost Wholesale analysis, variance analysis SR Accounting and monitoring for Whole Sale business. Managing auditors and handling regulatory requirements Working closely with cross functional team Monthly book closure activities and Trial balance analysis Subsidiaries companies' financial statements Wholesale TDS monitoring and coordination with operations and tax team Any other activities related to Wholesale financial reporting QUALIFICATION: Chartered Accountant EXPERIENCE: Minimum 5+ years of post qualification experience in accounting/ financial domain SKILLS AND COMPETENCIES: IND AS Experience with Financial Services Background Familiarity with RBI Regulations for NBFC EIR model working expertise and automation Excellent SAP/ERP knowledge, Microsoft Excel and power point Strong leadership skills and team player Good communication skills

Key Responsibility: End-to-End Model Development Design, train, and deploy machine learning models (supervised/unsupervised learning, NLP, time-series forecasting) using Python (scikit-learn, TensorFlow, PyTorch) and R for specialized statistical analysis. Optimize models for computational efficiency via parallelization, quantization, and cloud-native architectures (AWS SageMaker, GCP Vertex AI). Data Engineering & Pipeline Automation Build robust ETL/ELT pipelines for structured/unstructured data using SQL, Spark, and Apache Airflow. Implement feature engineering workflows and ensure data quality for large-scale datasets (1M+ records). Cross-Functional Collaboration Partner with product, risk, and engineering teams to operationalize models into business applications (e.g., credit risk systems, customer segmentation tools). Mentor junior engineers and lead code reviews to maintain best practices in MLops workflows. Model Governance & Compliance Develop monitoring frameworks for model drift, bias detection, and performance degradation. Ensure compliance with regulatory standards and internal governance policies. Innovation & Research Stay ahead of industry trends (e.g., LLMs, generative AI) and prototype solutions using no-code platforms. Publish internal white papers on novel methodologies and present findings to stakeholders. Technical Requirements Core Skills: Python (expert), R (intermediate), SQL, Apache Spark, Apache Arrow, Pydantic Machine Learning: Regression, classification, clustering, deep learning (CNNs, RNNs) Frameworks: scikit-learn, PyTorch, TensorFlow, Hugging Face, MLflow Cloud: AWS/GCP/Azure or any cloud platform, Docker, Kubernetes Domain Expertise (Preferred): Financial services (PD/LGD modelling, ECL calculations, risk analytics) Experience with no-code platforms is a bonus Knowledge of regulatory frameworks (Basel III, IFRS 9) Soft Skills & Culture Fit Ownership Mindset: Take end-to-end responsibility for projects, from ideation to deployment. Collaboration: Excel in cross-functional teams with clear communication to technical and non-technical stakeholders. Innovation: Continuously explore emerging tools (e.g., LLMs, AutoML) to solve business challenges.

Salary: 15 to 30 LPA Exp: 3 to 7 years Location: PAN India Notice: Immediate only..!! Key Skills: SAS, Credit Risk, risk analytics, MIS, risk reporting Roles and Responsibilities Extract, manipulate, and analyze large datasets from various sources such as Hive, SQL databases, and ETL processes. Develop and maintain dashboards using Tableau to provide insights on banking performance, market trends, and customer behavior. Collaborate with cross-functional teams to identify key performance indicators (KPIs) and develop data visualizations to drive business decisions. Desired Candidate Profile 3-8 years of experience in Data Analytics or related field with expertise in Banking Analytics, Credit risk . Strong proficiency in tools like SAS, Advance SQL knowledge preferred. Experience working with big data technologies like Hadoop ecosystem (Hive), Spark; familiarity with Python programming language required.

Get to know the team GrabFin is an aggregate of FinTech businesses spread across 6 countries in S.E. Asia, in the Lending, Payments and Insurance domains. We are excited to provide innovative financial services to all participants of the Grab Ecosystem be it our Drivers, Consumers or Merchants. Our products are built on fundamental market insights combined with data science and engineering to bring the best product market fit across the cross section of our user base. This understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers. The data scientist will work in a relatively flat team structure with an independent goal of building and manage critical data science models daily. You can expect to solve hard technical problems and grow into an expert on both batch and real-time Data Science use cases. You will have experience with technology and data science. You will be reporting to Senior Manager, Data Science. This role is onsite based in Bangalore. Youll develop credit risk scoring models for consumer loans, including PD, LGD, and collection models. Youll work with alternative data sources to boost model signal and accuracy. Your role will involve full ownership of the end-to-end model lifecycle from building and validation to deployment and maintenance. Youll collaborate with business, risk, and operations teams to shape solutions and influence product strategy with your insights. This is an individual contributor role suited for professionals with 8+ years of experience. The Critical Tasks You Will Perform Build predictive models using a mix of machine learning and traditional analytics methods to segregate between Good vs Bad borrowers Build Machine learning & Deep learning models to estimate losses from of a given portfolio. Validate models on new datasets, based on in-market performance. Engineer predictive features from internal data assets to build refined customer profiles. Identify external data assets to bring into the model mix. Drive model governance by collaborating with risk policy, compliance, and audit teams to ensure adherence to regulatory expectations. Identify model gaps or performance drifts and lead model refresh cycles. Present findings to senior leadership with clear articulation of risk trade-offs and growth. Translate model insights into strategic recommendations (e.g., policy changes, pricing levers, customer targeting strategies). Solve previously unsolved analytics problems using best in class data analytics and machine learning methodologies. Read more Skills you need The Essential Skills You Need 8+ years of experience. Strong understanding of credit business - lifecycle of a loan, collections process, and credit KPIs like NPL, ECL. Expert in building machine learning and predictive models in Python and Spark is an absolute must. SQL, Presto, Hive proficiency. Sound knowledge of machine learning concepts. Illustrative machine learning concepts/methods are: Bagging, Boosting, Regularisation, Online Learning, Recommendation Engines Experience with LLMs, and Generative AI Experience with model deployment pipelines - using MLFlow, Airflow, or other MLOps tools. Demonstrated experience building machine learning models Understand the trade-offs between model performance and our needs. Strong problem-solving mindset is critical for success in this role. Read more What we offer About Grab and Our Workplace Grab is Southeast Asias leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, weve got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility. Read more Life at Grab Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through lifes challenges. What we stand for at Grab We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique. #LI-DNI Read more

Get to know the team GrabFin is an aggregate of FinTech businesses spread across 6 countries in S.E. Asia, in the Lending, Payments and Insurance domains. We are excited to provide innovative financial services to all participants of the Grab Ecosystem be it our Drivers, Consumers or Merchants. Our products are built on fundamental market insights combined with data science and engineering to bring the best product market fit across the cross section of our user base. This understanding of our ecosystem combined with world class engineering execution continues to create tremendous value for our customers. The data scientist will work in a relatively flat team structure with an independent goal of building and manage critical data science models daily. You can expect to solve hard technical problems and grow into an expert on both batch and real-time Data Science use cases. You will have experience with technology and data science. You will be reporting to Senior Manager, Data Science. This role is onsite based in Bangalore. Youll develop credit risk scoring models for consumer loans, including PD, LGD, and collection models. Youll work with alternative data sources to boost model signal and accuracy. Your role will involve full ownership of the end-to-end model lifecycle from building and validation to deployment and maintenance. Youll collaborate with business, risk, and operations teams to shape solutions and influence product strategy with your insights. This is an individual contributor role suited for professionals with 8+ years of experience. The Critical Tasks You Will Perform Build predictive models using a mix of machine learning and traditional analytics methods to segregate between Good vs Bad borrowers Build Machine learning & Deep learning models to estimate losses from of a given portfolio. Validate models on new datasets, based on in-market performance. Engineer predictive features from internal data assets to build refined customer profiles. Identify external data assets to bring into the model mix. Drive model governance by collaborating with risk policy, compliance, and audit teams to ensure adherence to regulatory expectations. Identify model gaps or performance drifts and lead model refresh cycles. Present findings to senior leadership with clear articulation of risk trade-offs and growth. Translate model insights into strategic recommendations (e.g., policy changes, pricing levers, customer targeting strategies). Solve previously unsolved analytics problems using best in class data analytics and machine learning methodologies. Read more Skills you need The Essential Skills You Need 8+ years of experience. Strong understanding of credit business - lifecycle of a loan, collections process, and credit KPIs like NPL, ECL. Expert in building machine learning and predictive models in Python and Spark is an absolute must. SQL, Presto, Hive proficiency. Sound knowledge of machine learning concepts. Illustrative machine learning concepts/methods are: Bagging, Boosting, Regularisation, Online Learning, Recommendation Engines Experience with LLMs, and Generative AI Experience with model deployment pipelines - using MLFlow, Airflow, or other MLOps tools. Demonstrated experience building machine learning models Understand the trade-offs between model performance and our needs. Strong problem-solving mindset is critical for success in this role.

Function Finance & Accounts Role VP Finance & Accounts Reporting into Chief Finance Officer Key Result Areas 1. Filing of RBI returns (DNBS 01, 03, 4A, 4B, 10, 13 ) 2. Preparation of financials under IND AS 3. NBFC background knowledge of RBI guidelines applicable of middle lawyer company for accounting purpose 4. Accounting knowledge of assignment and PTC transaction under IND AS 5. Knowledge of financial planning and budgeting 6. Preparation of MIS 7. Knowledge of ECL calculation 8. Consolidation of Financials 9. Cost control and expenses analysis Required Skills Relevant experience with NBFC / HFC / Microfinance background Qualification CA No of years of Industry experience Atleast 10 years of relevant experience Role & responsibilities

Location: PAN India Immediate joiner required Experienced in end to end capital or Impairment process management RWA calculation engine using Standardized approach (BASEL 1/2/3) for Credit Risk Asset classification for Retail and Wholesale Products, Collateral Adjustment, on balance/ off balance exposure calculation Migration RWA calculation from BASEL 3 to 3.1 using Standardized or AIRB approach Knowledge of Banking domain/ banking products like Retail, corporate, banks, SME, Sovereign Project management / stakeholder management Keywords : Standardized approach - BASEL 1/2/3 Capital Reporting (Standardized approach) RWA Calculation Credit Risk (RWA) capital management

Develop and maintain mainframe applications using COBOL, JCL, DB2, CICS, and other mainframe technologies with 4+ years of experience,Write clean, efficient, and maintainable code. Required Candidate profile Perform troubleshooting, debugging, and resolution of technical issues related to mainframe applications.Work with business analysts and other team members to gather requirement

Salary: 15 to 30 LPA Exp: 3 to 8 years Location: Bangalore/Gurgaon/Pune Notice: Immediate only..!! Key Skills: SAS, Advance SQL, Credit Risk Roles and Responsibilities Extract, manipulate, and analyze large datasets from various sources such as Hive, SQL databases, and ETL processes. Develop and maintain dashboards using Tableau to provide insights on banking performance, market trends, and customer behavior. Collaborate with cross-functional teams to identify key performance indicators (KPIs) and develop data visualizations to drive business decisions. Desired Candidate Profile 3-8 years of experience in Data Analytics or related field with expertise in Banking Analytics, Credit risk . Strong proficiency in tools like SAS, Advance SQL knowledge preferred. Experience working with big data technologies like Hadoop ecosystem (Hive), Spark; familiarity with Python programming language required.