Director, Quantitative Modeling
Director, Quantitative Modelling
As a Director, Quantitative Modelling at Group Decision Science, you will be part of a team that’s building next generation analytics capabilities f to secure and enhance the financial wellbeing of people, customers and communities. We are applying cutting edge real-time banking technologies and modelling methodologies, utilizing standard and alternative data sources and leveraging recent developments in behavioural economics to bring fairly priced financial services to millions of underserved customers. Your efforts will enable financial inclusion for everyday people and small businesses across the globe making a tangible positive difference in their lives and the prosperity of local communities.
- Drive the innovation cycle by working with business and risk to identify the next opportunity and develop advanced analytics solutions that pushes forward our thinking
§ Lead the development of next generation models, scorecards, customer segmentation schemes, expert rules and other types of decision analytics to detect risks and improve returns by leveraging advanced statistical techniques and expert-based methodologies. Effectively manage their performance over the full cycle
§ Understand technical issues in modelling and apply these skills toward solving business problems.
§ Direct and actively participate in all stages of model development from data collection, model building, model validation, testing and calibration
§ Identify new opportunities and analyze a wide range of inputs, including quantitative data, use cases, and market research to improve models and decisions and business performance
§ Mine large multi-disciplinary data sets including credit bureau records, financial information, structured and unstructured data to gain deep business knowledge and insights of embedded relationships and customer behaviours
§ Manage projects activities
§ Plan, lead/collaborate with various internal and vendor teams, manage the model lifecycle, and provide periodic updates
§ Motivate and mentor associates to grow their skills and careers
§ Train line and operating personnel in model usage and problem detection.
§ Communicate technical subject matter clearly and concisely to individuals from various backgrounds
Skills and qualifications
- Communication excellence. You tell stories using data and analytics insights to energize the leadership, educate the peers, and empower the team.
- Intellectual curiosity. You ask difficult questions and don't take no for an answer. You contribute in team's brain storming sessions. Complex and unstructured problems and big data sets don't faze you but cause you to look for root causes.
- Action focus. You drive results by initiating action, trying things (and sometimes failing at them) through quick prototyping, and communicating to the team what works and what does not. You know how to find data, move it around, transform and fill in the gaps and implement your ideas through programming/statistical languages.
- Innovation. You look forward to the problem that are new to the industry. Both breakthroughs and continuous improvement of what we do makes your day
- Passion for data. You realize that your model, is 100% dependent on the data it is built from, or implemented on. You like pulling your own data, structuring it, and understanding the human and financial behaviors it represents
- PhD/Post Doc in any field with advanced quantitative focus or Masters or Bachelors degree with high distinction in modelling oriented discipline including but not limited to, Statistics, Mathematics, Psychometrics, Physics, Chemistry, Biology, Econometrics, Engineering, etc..
- Background and experience in small business or consumer risk or marketing, especially scoring models leveraging tradeline credit bureau data. You have dealt with these issues for at 7+ years while working for a leading international bank, credit bureau or information based company. For at least 3+ years, you have managed full model development lifecyle
- Strong understanding of predictive / analytical modelling techniques, theories, principles, and practices
§ Demonstrated capability turning “blackbox” algorithms into attributes and calculations appropriate for risk and pricing in a highly regulated bank
- Intensive experience in key econometric and statistical techniques (predictive modelling, logistic regression, survival analysis, panel data models, data mining methods, and other advanced statistical and econometric techniques)
- Strong hands-on knowledge of data mining / predictive modelling tools such as R, SAS, SPSS, Python, etc.
§ Strong familiarity and experience with data
§ Identification, sourcing and construction of large multi-disciplinary data sets including financial information, bureau records, structured and unstructured data
§ Preparation and processing of data including assessment of data quality, new variable creation, variable selection, etc.
§ Specific experience in leveraging credit bureau data and converting transactional data into attributes
- Ability and desire to mentor other modellers in the team on the art and science of modelling, data analysis, decision trade-offs between model complexity and model deployment
- Ability to conduct research into predictive / analytical modelling issues, practices, and products as required.