IIFL is Hiring!

Location: Mumbai

Experience: 2 years in Digital loans


Project Delivery

  1. Creating and monitoring proposals, SOWs, agreements to define and deliver projects.
  2. Go getter/Hustler attitude to identify the solutions and implementation inside and outside the organization
  3. Ensuring Exhaustive testing of feature is done before release having all sign-offs in place
  4. Managing and creating thorough BREDs and PRDs
  5. Keeping internal customers connected and fair KT is done amongst teams
  6. Managing the priorities of the tasks in pipeline -prioritize the priority
  7. Evaluating the impact of project delivery on top-line & Bottom line of the company

Digitization – Loan Life Cycle

  1. Pre-Disbursement Customer life cycle is digitized with being compliant to all regulations.
  2. Post Disbursement Customer life cycle is digitized with being compliant to all regulations.
  3. Concocting and consuming all business logic algorithms to make the journey smooth.
  4. Ensuring all necessary and requisite data is captured to underwrite the loan keeping Credit & Operational risk minimum
  5. UI/UX Enhancement for internal & External stakeholders through life cycle
  6. Conduct Secondary Research to improve the product continuously by staying up to date with market standards
  7. Improving Loan Origination Software continuously to inculcate ever changing environment and technological advancements.

Business Support

  1. Ensuring all required services are running smoothly. Debug & resolve the issue if not.
  2. One point contact for all business and technical know-how for all internal stakeholders
  3. Suggesting the most feasible and economical approach to a problem statement to management.
  4. Act as buffer between technology team & Business teams to ensure coordination.

Location: Bengaluru (on-site)

Experience: Minimum 5 years


  1. Work closely with product and operation teams to implement new Models using ML/DL.
  2. Develop highly scalable predictive models and tools leveraging machine learning, deep learning, and rules-based models in areas of Risk, Fraud, and Collection
  3. Build state-of-the-art risk models using alternative data such as device data, network data, etc.
  4. On the Data Science model end-to-end, from data collection to model building, to monitoring the model in production
  5. Build Machine Learning and Deep Learning models in the customer lifecycle which include Personalization, Recommendation, Rewards, Referrals, Transaction Categorization, and Customer Science-related models
  6. Understands the End to End ML pipeline ( data gathering to production )
  7. Conduct Data Analyses; your analyses will decide which policies we adopt, where we expand our business, and with whom we partner


  1. Bachelors or Master’s degree in Computer Science, Information management, Statistics, or related field, with 5+ years of relevant work experience.
  2. Experience in risk specifically in fraud risk at alternative lending, SME, payment, credit card, Loan Product, or top-tier consultancy companies
  3. Python programming skill is a must. Strong coding capabilities in ML and Deep learning
  4. Experience in statistical modeling, machine learning, data mining, unstructured data analytics, and natural language processing. Sound understanding of – Bayesian Modeling, Classification Models, Cluster Analysis, Neural Networks, Nonparametric Methods, Multivariate Statistics, etc.
  5. Strong in data analysis and data wrangling
  6. Experience with common libraries and frameworks in data science
  7. Familiarity with database queries and data analysis processes (SQL, Python)

Location: Bengaluru

Experience: Minimum 4 years


  1. Developing credit risk Strategy that will determine loan eligibility, as well as repayment/default predictions
  2. Work with lending partners to co-develop/agree on credit risk models
  3. Develop, implement, and monitor risk strategies cutting across credit underwriting, limit assessment, pricing, line management, and collections
  4. Develop models to determine pricing and interest rates to balance potential gains with risks
  5. Developing, deploying, and iterating on risk experiments to create better risk model
  6. Set up a robust monitoring and alerting systems on early warning signals to drive agility in decision-making
  7. Help shape the product design and operations processes by evaluating them from a credit risk lens
  8. Conducting end-to-end analytical processes to find answers to business problems, from data preparation, and exploratory data analysis, up to testing hypotheses both by doing observational and/or experimental analysis
  9. Work closely with collections to ensure the feedback loop is closed and learnings are relayed into our credit decision strategies
  10. Craft automated dashboards to track metrics on risk strategy and portfolio performance
  11. Perform ad-hoc reporting and analysis, when needed
  12. Recruit, train, develop and guide juniors in the team
  13. Managing multiple projects simultaneously
  14. Worked on wider variety of problem statement in Digital Lending in area of Risk, Marketing, Fraud and Collection etc


  1. B – tech/ BE/IIT preferred
  2. Lead: with Experience of 6 + years & Senior Manager with Experience of 4+ Years
  3. 4+ years of credit risk policy making using Data and analytics experience with at least 2 years in a Fintech start up (SME lending preferred)
  4. Proven track record in solving ambiguous problems with a structured approach
  5. Strong track record in solving analytical problems using quantitative and statistical approaches
  6. Preferred experience in SQL in any flavor (preferably Big Query and MySQL) and able to write an efficient query
  7. Extensive Use of Python
  8. Work experience and knowledge of more than one of these domains is a plus: Risk Analytics, Credit Risk, Portfolio Analytics, and/or Lending Business
  9. Highly motivated people who are focused on winning by combining great teamwork, rapid execution, and an uncompromising approach to quality and customer satisfaction

Location: Mumbai

Experience: Minimum 4 years (Residential/Commercial projects )

Roles & Responsibilities:

  1. Appraisal and Structuring of Real Estate funding transactions
  2. Preparing Credit Appraisal Memos for evaluating credit risk in borrower, transaction & underlying security.
  3. Interaction with in-house team (Technical, Legal etc) to provide solution to clients in coordinated and timely manner.
  4. Interaction with clients in real estate space to understand their business model, organization structure and financing needs
  5. Preparing term sheets and ensure compliance with sanctioned terms
  6. Preparation of financial models for the transactions
  7. Ensuring compliance of loan accounts with regulatory guidelines and internal credit and company guidelines
  8. Monitoring and proactively highlighting risk in the portfolio of loans or the underlying security or the client
  9. Keeping update on real estate micro-markets, real estate developers, regulations pertaining to the sector

Key Skills:

  1. Experience in Residential/Commercial projects 
  2. Knowledge of credit appraisal/underwriting side in Real Estate business

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