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Sr. Data Scientist Quantitative Modeling

Location : New York, NY
Job Type : Direct
Hours : Full Time
Travel : No
Relocation : No

Job Description :
Required Qualifications :


As a Quantitative Modelling/Data Science Senior Associate at Group Decision Science, you’ll be part of a team that’s building next generation risk/reward models and analytics capabilities for this top-10 global bank, applying the 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 situations, develop hypotheses, integrate internal and external data sources, analyse them using cutting edge machine learning or statistical modelling techniques to uncover causality and synthesise insights

  • Combine, clean, manipulate and investigate large data sets including financial information, bureau records,  structured (e.g., transactional data) and unstructured data (e.g., communication meta-data and referential information) in order to create attributes that are leverageable in statistical analysis and gain deep business insights into customer behaviours

  • Create models for all phases of the customer life cycle using the appropriate unguided, semi-guided and guided parametric and non-parametric modelling techniques to manage risks and improve returns for the bank

  • Investigate the applicability of new computing technologies and cutting edge analytical techniques to banking

  • Understand, adapt and fine-tune latest developments in machine learning and statistical modelling techniques in order to apply them appropriately to solve business problems

  • Propose innovative modelling solutions, evaluate their effectiveness through proof of concept experimentations and refine and enhance them as necessary

  • Build scalable solutions that create great business impact and provide support for their implementation

  • Communicate technical subject matter clearly and concisely to individuals from various backgrounds

  • Provide consulting support to internal business units enabling effective application of analytic solutions to their strategies 


Ideal Attributes:             

  • Intellectual curiosity. You ask difficult questions and don’t take no for an answer.  You contribute to team brain storming sessions, criticise ideas and look forward to getting feedback on your ideas.  Unstructured problems and big data sets don’t faze you but cause you to look for your own solutions. 

  • 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 problems that are new to the industry.  Both breakthroughs and continuous improvement of what we do makes your day.

  • Passion for data. You like pulling your own data, structuring it, cleaning it, and understanding the human and financial behaviours it represents.

  • Continuous learner.  Willingness and desire to learn from other data scientists and modellers in the team on the art and science of modelling, feature engineering, and trade-offs between model complexity and practical implications including deployment, interpretability and stability.


Basic Qualifications:

  • PhD/Post Doc in any field with advanced quantitative focus or Masters in modelling oriented discipline including but not limited to Machine Learning, Statistics, Psychometrics Mathematics, Physics, Chemistry, Biology, Bioinformatics, Econometrics, Engineering, Neuroscience, Computer Science etc.

  • 2-3 years of post-graduate experience in the field of advanced quantitative techniques while working for leading global academic institutes or corporate research labs or analytics organizations of large corporations or in consulting companies in analytics roles

  • Blend of understanding of big data technologies with strong knowledge of a wide array of predictive modelling methods. Additionally, you must be skilled at clearly communicating your findings and translating them into practical solutions.

  • Background and experience in small business or consumer risk or marketing, especially scoring and forecasting models

  • Strong familiarity and experience with data preparation and processing - such as assessment of data quality, feature engineering, variable selection, etc. Specific experience in converting transactional data into attributes desired.

  • Deep programming skills and  3+ years’ experience in R, Perl, Python, or other languages appropriate for large scale analysis of numerical and textual data

  • Excellent interpersonal and collaboration skills, ability to explain complicated mathematical concepts, algorithms and data structures to all business partners

  • Experience in analysis on big data platforms is a plus

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