17 Ecl Jobs

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.

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

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

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.

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.

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.

Role Competencies - Experienced in development of credit risk models for BASEL reporting, PD, LGD, EAD and/ stress testing or should be well versed with understanding of these concepts Skilled in development of internal and external risk models by computing standard metrics Skilled in developing and analyzing product-specific solutions within banking domain varying across underwriting/monitoring loan portfolios, developing collections scorecards, loss forecasting amongst others Ability to work with key stakeholders across businesses, client portfolio teams to derive insights and calibrate model performance Ability to present the findings of the analysis to stakeholders and hold presentations for a larger audience Ability to drive discussions with the stakeholders and present the findings / summary of the project activities

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.

Role & responsibilities - ECL: Calculation: To calculate ECL for LC, MM, MEG, SEG, SCF, DIG SCF, CMG-Insti, CMG Retail, Digital, Unsecured, Mortgage. Automation: To implement ECL Automation project using Python. Build and maintain ECL model and documentation: Development of Probability of Default models used in the computation of ECL for organization (secured and unsecured) portfolios in accordance with Ind AS 109/IFRS 9 guidelines. Design, develop, test and validate statistical models for the entire product suite. Responsible for the documentation of PD, LGD models and the ECL Policy. Computation: Responsible for enhancing and developing the Internal Capital Adequacy Assessment Process (ICAAP) in the organization. This involves stress testing of risk in excess of the Pillar 1 requirement including credit risk, liquidity risk, IRBB, operational risk and strategic risk. Model Development: Development of stress testing models in compliance with the regulatory guidelines. Documentation Responsible for the documentation of ICAAP. Risk Appetite Statement/Enterprise Risk: Computation of various risk types on the basis on key risk metrics. Aggregate the various risk types to compute an Enterprise Risk score. Build Model and maintain documentation and track necessary deliverables 3. VAR: Model Development: Design, develop and test VAR Models. Model Validation: Perform Back-testing and sensitivity analysis of VAR model. Documentation: Prepare and maintain documentation for the VAR mode 4. Sensitivity Analysis on various portfolio cuts: Statutory/Internal Audit: To support Audit closure for LC, MM, MEG, SEG, SCF, DIG SCF, CMG-Insti, CMG Retail, Digital, Unsecured, Mortgage. RBI Audit: To help in closing RBI audit.

Credit Risk ECL - NBFC - Thane Job Purpose: ECL: Calculation: To calculate ECL for LC, MM, MEG, SEG, SCF, DIG SCF, CMG-Insti, CMG Retail, Digital, Unsecured, Mortgage. Automation: To implement ECL Automation project using Python. Build and maintain ECL model and documentation: Development of Probability of Default models used in the computation of ECL (secured and unsecured) portfolios in accordance with Ind AS 109/IFRS 9 guidelines. Design, develop, test and validate statistical models for the entire product suite. Responsible for the documentation of PD, LGD models and the ECL Policy. ICAAP: Computation: Responsible for enhancing and developing the Internal Capital Adequacy Assessment Process (ICAAP). This involves stress testing of risk in excess of the Pillar 1 requirement including credit risk, liquidity risk, IRBB, operational risk and strategic risk. Model Development: Development of stress testing models in compliance with the regulatory guidelines. Documentation Responsible for the documentation of ICAAP. Risk Appetite Statement/Enterprise Risk: Computation of various risk types on the basis on key risk metrics. Aggregate the various risk types to compute an Enterprise Risk score. Build Model and maintain documentation and track necessary deliverables VAR: Model Development: Design, develop and test VAR Models. Model Validation: Perform Back-testing and sensitivity analysis of VAR model. Documentation: Prepare and maintain documentation for the VAR model. Sensitivity Analysis on various portfolio cuts: Perform Sensitivity Analysis on various portfolio cuts. Audit Closure: Statutory/Internal Audit: To support Audit closure for LC, MM, MEG, SEG, SCF, DIG SCF, CMG-Insti, CMG Retail, Digital, Unsecured, Mortgage. RBI Audit: To help in closing RBI audit.

We are looking for a highly skilled and experienced professional to join our dynamic Risk Department If you are a strategic thinker with a deep understanding of financial risk management, particularly in the microfinance sector , and have significant experience in Credit Risk , Market Risk , Asset Liability Management (ALM) , and Expected Credit Loss (ECL) , we would love to hear from you. Key Responsibilities: Credit Risk Management: Assess and monitor credit risk exposure across the organization, including portfolios in microfinance and MSMEs, and develop models to predict and manage risks. Expected Credit Loss (ECL): Oversee ECL models and ensure compliance with IFRS 9 . Collaborate with internal teams for accurate reporting and backtesting. Liquidity and Market Risk: Prepare and monitor LCR , evaluate market risk factors, and optimize funding strategies in collaboration with treasury and finance teams. Internal Capital Adequacy Assessment Process (ICAAP): Assist with ICAAP execution, ensuring capital adequacy and performing stress testing and scenario analysis. Risk Monitoring & Governance: Lead risk assessments, monitor KRIs , and ensure regulatory compliance while identifying risk mitigation strategies. Qualifications: Education: CA, MBA (Finance/Economics), and relevant Risk Management certifications (FRM, CRM). Experience: Minimum 10-12 years of experience in risk management , with at least 5-6 years in microfinance , lending operations , and RBI compliances . Skills: Strong leadership, strategic thinking, communication skills, and problem-solving abilities. Location: Gurugram Salary & Benefits: Competitive salary and benefits package, commensurate with experience. To Apply: If interested, Please send your resume to Pooja.jain@satincreditcare.com

Collections strategy Forecasting Budgeting for entire year on ECL NCL losses at product level Highlight reporting various snapshot, region wise, team wise, stage wise etc Target Setting basis historical performance and delivery of ECL performance Communicate and liaise with NCH Strategy, National Collections Manager and counterparts with other Risk Management functions, on market intelligence and / or Risk Analysis and segmentation of portfolios to implement risk-based strategy for maximizing collections efficiencies. Collections Analytics Lead customer risk segmentation with internal data points as well as bureau data Prepare forecasting models for bounce stocks for all retail products. Work closely with NCMs, Risk Policy, Underwriting for enhanced Analytics Models Ensure analytics-driven ACR (accounts to collectibles ratio) and allocations strategy to ensure cost and resource optimization MIS Work with risk policy, underwriting team, NCMs and business heads towards ECL Management and decks Develop Balance Score Cards and lead Monthly Target Setting exercises Reporting Manage high standards of portfolio quality during as part of retail expansion strategy To Ensure high accuracy of MIS reporting and reconciliation with BIU and Operations

He had to work 8 hrs duty in Reputed flexible pkg company. in various department Like Rotograuvre printing, Extrusion coating, Blown film , slitting, Lamination , QC etc . In shift schedule. URGENT FOR SILVASSA/VAPI Required Candidate profile Candiadte should be ITI-DIPLOMA-DPT-CIPET- BA-BCOM-BSC FOR SILVASSA URGENT Trainee job for flexible packaging industry duty-8 hrs. Salary- RS-14800 ctc- Net-11900 Probation- 1 year . Increment

Roles and Responsibilities Manage financial statements, including balance sheet, income statement, cash flow statement, and notes to accounts. Prepare quarterly GST returns (BAS) and monthly TDS returns. Ensure compliance with Income Tax Returns (ITR), Ind AS, ECL, NBFC regulations. Conduct audits of books of accounts and prepare MIS reports. Review internal controls and processes to ensure accuracy and efficiency. Prepare monthly borrowing workings in compliance with Ind AS standards, and account for borrowing costs for financial reporting, statutory audits, internal audits, and due diligence processes. Calculate and prepare monthly Effective Interest Rate (EIR) workings for loans and borrowings. Prepare and account for Direct Assignment and Securitization transactions as per Ind As requirements Desired Candidate Profile 2-3 years of experience in finance & accounting with a focus on NBFC industry. CA qualification preferred but not mandatory; advanced Excel skills required. Strong understanding of accountancy principles, taxation laws, and regulatory requirements.

Company: Analytics Saves at Work is looking for a Credit Specialist for a client in the BFSI sector. This role requires a deep understanding of Credit & Lending within banking, with expertise in data analytics and risk management frameworks. The ideal candidate will help drive data-driven decision-making, improve credit assessment processes, and enhance customer outcomes. Roles & Responsibilities: Convert business challenges into analytical problems and deliver data-driven solutions. Strong understanding of Credit & Lending processes within Wholesale Banking. Conduct in-depth analysis to provide high-quality insights and recommendations for credit risk management. Design data-driven solutions for credit risk assessment across multiple businesses/regions to improve decision-making. Drive efficiency gains and process enhancements in credit evaluation and risk assessment. Utilize data to improve credit approval processes and customer outcomes through insights and analytics. Identify, assess, and mitigate risks associated with credit portfolios. Work on business benefit initiatives through self-initiated projects related to credit risk and lending. Requirements: Minimum of 4 years of experience in Credit & Lending analysis. Strong background in Wholesale Banking with exposure to Credit Risk Frameworks such as Basel II, Basel III, IFRS 9, and Stress Testing. Hands-on experience in advanced programming languages such as Python (Pandas, Numpy) or PySpark. Expertise in data processing, ETL, SQL, Hive/Spark SQL, and Data Warehousing. Experience with risk and analytics applications in credit and lending. Prior exposure to Agile methodology and project management tools like Jira, Confluence, and GitHub. Strong communication and interpersonal skills for liaising with business teams and stakeholders.