We are looking for a highly motivated and experienced Data Scientist to assist with developing the next-generation AI/ML operational platforms for Credit Risk/rating Modeling. The role will require hands-on experience with development of Consumer Credit Rating Models and its optimization, automation of Credit rating scorecard models, specifying machine learning workflows, feature extraction/feature definition, data validation, and model lifecycle management.
Job Title: Data Scientist
Designation: Data Scientist
Reports to: Head of Engineering
Location: Bakhundole, Lalitpur, Nepal
Shift: Standard (09:00 to 06:00 PM – EST) from Monday to Friday
We are looking for a highly motivated and experienced Data Scientist to assist with developing the next-generation AI/ML operational platforms for Credit Risk/rating Modeling. The role will require hands-on experience with the development of Consumer Credit Rating Models and their optimization, automation of Credit rating scorecard models, specifying machine learning workflows, feature extraction/feature definition, data validation, and model lifecycle management. The candidate must have a deep understanding of Credit rating scorecard modeling and AI/ML modeling. He/she should be willing to mentor junior analysts and lead an analytical project from inception to implementation and be able to partner with technology teams to bring models to production.
Roles and Responsibilities
- Deliver customized solutions across the customer lifecycle for financial institutions. This includes but is not limited to the development of customer management scorecards of application, behavioral and collection risk scorecards, FICO, Basel III PD, CCF and LGD models, customer life cycle strategies of approval, limit, price and early warning.
- Activity participant in model development project from an end-to-end perspective including formulating the data extraction requirements, data cleaning, credit risk model development, model validation, implementation testing and performance monitoring
- Analyze data to extract risk analytics patterns, identify emerging trends, and present detailed metrics of overall risk management solution effectiveness.
- Creating a platform to automate every step of the ML Process from Data Prep, Model Building, Deployment, and Operations, and which utilizes machine learning in the platform itself.
- Development & deployment of high quality operational credit risk models
- Build & implement credit scoring (full lifecycle) models using internal and external data sources
- Selecting the best algorithmic approach to serve and Optimization of Credit Rating models
- Comparing multiple models in production and selecting the best model to serve a given use case
- Apply statistical analysis, machine learning techniques, predictive modeling, and data mining to solve business problems in credit Risk/rating.
- Develop loss forecasts to reflect credit policy and/or segmentation changes and establish loss thresholds for various products
- Develop processes for regular reporting and monitoring of credit risk exposure
- Remain up-to-date on regulatory changes and landscape, best practices and cutting-edge developments in the industry
- Continuously assess the need and usage of new data sources to enhance credit models in the future
Skills and Qualifications
- Task Related and Certifications
- Masters degree in a related quantitative field (Computer Science, Math, Statistics, Engineering, Physics, Economics)
- 5+ years of relevant working experience in a similar role, preferably involving Credit Risk/Rating Scorecard Modeling.
- Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and statistical/mathematical programming languages (e.g. Python, R, SAS).
- Experience with Machine learning methods such as Neural Networks, Clustering, SVM, Ensemble models, Random Forest, and Gradient Boosting
- Demonstrated Knowledge of Databases (Hadoop preferred), Data ETL (Spark preferred – streaming and structured streaming), Analytics, ML Libraries (scikit-learn, Pytorch, Keras, XGBoost, Tensorflow).
- Strong software design and enterprise architecture skills, particularly with AWS services
- A solid grounding in statistics, probability theory, data modeling, machine learning algorithms, and software development techniques and languages used to implement analytics solutions
- A solid grounding in statistics, probability theory, data modeling, machine learning algorithms, and software development techniques and languages used to implement analytics solutions.
- Competencies and Soft Skills
- Able to work to conflicting deadlines while maintaining accuracy and quality
- Excellent time management and organizational skills
- Understanding of security best practices
- Strong sense of personal responsibility and accountability for delivering high-quality work
- Attention to detail, and written and verbal communication skills
- Must have excellent documentation skills
- PhD degree in a related quantitative field (Computer Science, Financial Engineering, Math, Statistics, Engineering, Physics, Economics).
- Experience with large data using Spark, Hadoop, or similar technologies.
- Past experience in experian, equifax or similar industry is highly preferred.
- Experience with Commercial/Consumer Credit rating Models
- Knowledge of Time Series Econometric models
- Experience with cloud-based platforms
- Prior people mentoring or leading experience of fellow Machine Learning and Data Science Analysts
- Relevant experience in operational credit modeling within an FCA regulated company
What We Offer
- 5 working days in a week (09:00 am-06:00 pm)
- Work in a multinational company operating in the Cloud & ICT domain, based out of the UK and operating in Finland, Australia, India, Nepal, Pakistan, Bangladesh & Srilanka
- Best in class open, progressive, professional, and equal opportunity work environment
- Closely knit and supportive team members and a culture where your contributions, opinions, and diversity is welcome, respected, & encouraged
- Exposure to multi-disciplinary skill areas (including team management & leadership) in a vibrant start-up ecosystem with deep work involving world-class leaders like Amazon, Microsoft, Google, Zoom, Alibaba, DigitalOcean, and Facebook
- Opportunity to travel regionally (as part of assignment/ training and development or delivery ) in Nepal, India, Pakistan, Bangladesh, or Srilanka
How to apply?
Suitable candidates meeting the above criteria are requested to send their CV and cover letter to email@example.com
Only shortlisted candidates will be invited for the further selection process. You are requested to clearly mention the position you are applying for in the subject of the email.