The ideal candidate is a rare hybrid, a computer scientist with the programming abilities to scrape, combine, and manage data from a variety of sources and a statistician who knows how to derive insights from the information within. He or she will combine the skills to create new prototypes with the creativity and thoroughness to ask and answer the deepest questions about the data, what secrets it holds, and to push the boundaries of what is possible with big data. Qualified candidates will have a strong academic background in mathematics or statistics, passion for data science, data mining, machine learning and experience with big data architecture and methods.
- Research innovative data solutions to solve real market problems.
- Drive the creation of new models and capabilities that will leapfrog traditional bureau based modeling done at most major financial institutions leveraging a wide array of data from both traditional (credit bureaus) and nontraditional (data aggregators & other) sources.
- Conceptualize, analyze and develop actionable recommendations for strategic challenges facing the organization.
- Work with key stakeholders and understand their needs to develop new or improve existing solutions around data and analytics.
- Develop analytical approaches to meet business requirements; this involves translating requests into use cases, test cases, preparation of training data sets and iterative algorithm development.
- Manage data analysis to develop fact-based recommendations for innovation projects.
- Mine Big Data and other unstructured data to tap untouched data sources and deliver insight into new and emerging solutions.
- Work with cross-functional teams to develop ideas and execute business plans.
- Remain current on new developments in data analytics, Big Data, predictive analytics, and technology.
- Advanced degree in a quantitative field (Statistics, Mathematics, Economics, etc.)
- 2+ years experience in modeling and predictive analytics with experience working with unstructured data
- Excellent problem solving skills with the ability to design algorithms, which may include data cleaning, data mining, data clustering and pattern recognition methodologies
- Strong skills in statistical analyses with abilities in advanced data management and statistical programming using SAS, and R
- Experience designing and implementing Big Data solutions
- Experience in customer scoring, risk modeling, credit scoring, fraud detection, causal analysis, and pattern recognition Familiarity with Agile methodology
- Ability to work cross-functionally in a highly matrix driven organization, at times under ambiguous circumstances
- Experience with a range of big data architectures
- Broad understanding and experience of real-time analytics
- Proven research background, in industry work or academia, with an emphasis on delivering research that has a critical impact on multiple projects
- Provide a unique blend of skills that both unlock the insights of data and tell a fantastic story through the data
- Ability to use a hands on approach to integrate math, algorithms, and an understanding of human behavior to answer difficult ad-hoc human questions
- Ability to rapidly prototype solutions by combing background in computer science with statistics to derive insights from populations of information
- Personal qualities desired: creativity, tenacity, curiosity, and passion for deep technical excellence
Please send your latest CV to email email@example.com with subject Data Scientist latest 28 February 2017