IIFL is Hiring!
Experience: 2 years in Digital loans
- Creating and monitoring proposals, SOWs, agreements to define and deliver projects.
- Go getter/Hustler attitude to identify the solutions and implementation inside and outside the organization
- Ensuring Exhaustive testing of feature is done before release having all sign-offs in place
- Managing and creating thorough BREDs and PRDs
- Keeping internal customers connected and fair KT is done amongst teams
- Managing the priorities of the tasks in pipeline -prioritize the priority
- Evaluating the impact of project delivery on top-line & Bottom line of the company
Digitization – Loan Life Cycle
- Pre-Disbursement Customer life cycle is digitized with being compliant to all regulations.
- Post Disbursement Customer life cycle is digitized with being compliant to all regulations.
- Concocting and consuming all business logic algorithms to make the journey smooth.
- Ensuring all necessary and requisite data is captured to underwrite the loan keeping Credit & Operational risk minimum
- UI/UX Enhancement for internal & External stakeholders through life cycle
- Conduct Secondary Research to improve the product continuously by staying up to date with market standards
- Improving Loan Origination Software continuously to inculcate ever changing environment and technological advancements.
- Ensuring all required services are running smoothly. Debug & resolve the issue if not.
- One point contact for all business and technical know-how for all internal stakeholders
- Suggesting the most feasible and economical approach to a problem statement to management.
- Act as buffer between technology team & Business teams to ensure coordination.
Location: Bengaluru (on-site)
Experience: Minimum 5 years
- Work closely with product and operation teams to implement new Models using ML/DL.
- Develop highly scalable predictive models and tools leveraging machine learning, deep learning, and rules-based models in areas of Risk, Fraud, and Collection
- Build state-of-the-art risk models using alternative data such as device data, network data, etc.
- On the Data Science model end-to-end, from data collection to model building, to monitoring the model in production
- Build Machine Learning and Deep Learning models in the customer lifecycle which include Personalization, Recommendation, Rewards, Referrals, Transaction Categorization, and Customer Science-related models
- Understands the End to End ML pipeline ( data gathering to production )
- Conduct Data Analyses; your analyses will decide which policies we adopt, where we expand our business, and with whom we partner
- Bachelors or Master’s degree in Computer Science, Information management, Statistics, or related field, with 5+ years of relevant work experience.
- Experience in risk specifically in fraud risk at alternative lending, SME, payment, credit card, Loan Product, or top-tier consultancy companies
- Python programming skill is a must. Strong coding capabilities in ML and Deep learning
- 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.
- Strong in data analysis and data wrangling
- Experience with common libraries and frameworks in data science
- Familiarity with database queries and data analysis processes (SQL, Python)
Experience: Minimum 4 years
- Developing credit risk Strategy that will determine loan eligibility, as well as repayment/default predictions
- Work with lending partners to co-develop/agree on credit risk models
- Develop, implement, and monitor risk strategies cutting across credit underwriting, limit assessment, pricing, line management, and collections
- Develop models to determine pricing and interest rates to balance potential gains with risks
- Developing, deploying, and iterating on risk experiments to create better risk model
- Set up a robust monitoring and alerting systems on early warning signals to drive agility in decision-making
- Help shape the product design and operations processes by evaluating them from a credit risk lens
- 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
- Work closely with collections to ensure the feedback loop is closed and learnings are relayed into our credit decision strategies
- Craft automated dashboards to track metrics on risk strategy and portfolio performance
- Perform ad-hoc reporting and analysis, when needed
- Recruit, train, develop and guide juniors in the team
- Managing multiple projects simultaneously
- Worked on wider variety of problem statement in Digital Lending in area of Risk, Marketing, Fraud and Collection etc
- B – tech/ BE/IIT preferred
- Lead: with Experience of 6 + years & Senior Manager with Experience of 4+ Years
- 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)
- Proven track record in solving ambiguous problems with a structured approach
- Strong track record in solving analytical problems using quantitative and statistical approaches
- Preferred experience in SQL in any flavor (preferably Big Query and MySQL) and able to write an efficient query
- Extensive Use of Python
- Work experience and knowledge of more than one of these domains is a plus: Risk Analytics, Credit Risk, Portfolio Analytics, and/or Lending Business
- Highly motivated people who are focused on winning by combining great teamwork, rapid execution, and an uncompromising approach to quality and customer satisfaction
Experience: Minimum 4 years (Residential/Commercial projects )
Roles & Responsibilities:
- Appraisal and Structuring of Real Estate funding transactions
- Preparing Credit Appraisal Memos for evaluating credit risk in borrower, transaction & underlying security.
- Interaction with in-house team (Technical, Legal etc) to provide solution to clients in coordinated and timely manner.
- Interaction with clients in real estate space to understand their business model, organization structure and financing needs
- Preparing term sheets and ensure compliance with sanctioned terms
- Preparation of financial models for the transactions
- Ensuring compliance of loan accounts with regulatory guidelines and internal credit and company guidelines
- Monitoring and proactively highlighting risk in the portfolio of loans or the underlying security or the client
- Keeping update on real estate micro-markets, real estate developers, regulations pertaining to the sector
- Experience in Residential/Commercial projects
- Knowledge of credit appraisal/underwriting side in Real Estate business