Director, Data Science
As Director, Data Science at Group Decision Science, you’ll be part of a team that’s building next generation information and analytics capabilities. Applying cutting edge in real time banking technologies, using transaction information for tens of millions of customers, and leveraging alternative data sources to secure and enhance the financial wellbeing of people, customers and communities. Your efforts will enable financial inclusion for everyday people and small businesses across the globe making a tangible positive difference in their lives and prosperity of local communities.
· Understand complex business challenges, develop hypotheses, integrate internal and external data sources, analyze them using cutting edge machine learning or statistical modelling techniques to uncover causality (i.e., we go beyond correlations and interesting trends in making decisions that affect people’s financial wellbeing) and synthesizing insights
· Propose innovative modelling solutions, evaluate their effectiveness through proof of concept experimentations and refine and enhance them as necessary to ensure scalability and provide support for their implementation.
· Create new models through entire life cycle using the most effective application of supervised, semi-supervised and unsupervised parametric and non-parametric modeling methods.
· Investigate the impact of new computing technologies and niche, cutting edge analytical techniques and specialized applications, on the future of banking
· Drive, understand, and adapt latest developments in machine learning and statistical modelling and apply them appropriately to solve business problems.
· Clean, manipulate and investigate large data sets
· Intellectual curiosity. You ask difficult questions and don’t take no for an answer. You contribute in team’s brain storming sessions, provide input on the team’s ideas and look forward to getting feedback on your ideas! 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 taking accountability for 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. Strong academic record and publications in journals or notable outcomes in data science competitions. 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 mathematical representation of reality which we call a model, is 100% dependent on the data it is built from, or implemented on. You like pulling your own data, structuring it, cleaning it and understanding the human and financial behaviors it represents.
· PhD/Post Doc in any field with advanced quantitative focus in modelling oriented discipline including but not limited to Machine learning, Statistics, Psychometrics, Mathematics, Physics, Chemistry, Biology, Bioinformatics, Econometrics, Neuroscience, Computer Science.
· 8+ years of analytical experience including 5 years of post-PhD experience in the field of advanced quantitative techniques while working for leading global academic institutes or corporate innovation research labs or analytics organizations of large corporate or in consulting companies in analytics roles.
· Nice blend of big data technologies coupled with strong knowledge of predictive modeling methods! Additionally, you must be skilled at clearly communicating your findings and translating them into practical solutions.
Sound knowledge and application in the following:
· Advanced statistical methods including complex multivariate statistical methods, discrete choice modelling, conjoint based analysis
· Advance knowledge of machine learning methods including classification, regression and clustering methods
· Knowledge of heuristic methods and optimization techniques including system modeling and simulations.
· Deep programming skills and 5+ years’ experience in R, Perl, Python, or other languages appropriate for large scale analysis of numerical and categorical data
· Advanced quantitative methods relevant to modelling risk and consumer behavior: both parametric and non-parametric modelling, using unguided, semi-guided and guided approaches as appropriate.
· Willingness and desire to learn from other data scientists and modellers in the team on the art and science of modelling, feature engineering, decision trade-offs between model complexity and model deployment
· Excellent prototyping skills
· Excellent interpersonal and collaboration skills, ability to explain complicated mathematical concepts, algorithms and data structures to all business partners
· Experience with graph algorithms such as semi-supervised learning on graphs, graph clustering, community detection, interest/topic graphs, and social network analysis
· Knowledge of emerging platforms