Data Scientist at LenddoEFL
About the Position:
LenddoEFL is seeking an experienced Data Scientist to execute and improve our modeling efforts with an innovative, challenging alternative to traditional credit scoring. As a Data Scientist on LenddoEFL’s modeling team, you will be responsible for building, monitoring and deploying different types of models. The team works on non-traditional credit scoring techniques and is continuously looking for improvement on its standards.
- Work with research scientists/engineers to develop, prototype and productize new machine learning and graph algorithms operating on wide and big data.
- Design scalable big data pipeline/workflows for behavioral and social algorithms.
- Build strong communication channels with different stakeholders
- Review and analyze client and external data sets.
- Deploy and integrate LenddoEFL's solutions in clients’ environments.
- Establish and implement the risk frameworks including design variables and scorecards, model validation and portfolio performance monitoring.
- Design, build and implement Data Manipulation environments for internal and external purposes
- Rapid identification of R&D opportunities and model improvement.
- Research new non-traditional sources of data to include in the LenddoEFL platform.
- Advanced degrees in Applied Math, Statistics, Engineering or equivalent
- 5+ years of job experience with statistical modeling
- Strong programming skills.
- Experience with statistical techniques and tools in python or R.
- Good communication skills; prefer candidates who have experience of presenting technical concepts and results to risk and business teams.
- Plays well with others; able to listen to, appreciate, and effectively critique peers’ opinions.
- Proven experience in Data manipulation. Database skills in any major database language.
- Deep fundamental understanding in the technical aspects, monitoring and evaluation techniques, and the challenges associated with traditional credit scoring.
- Demonstrated interest in machine learning and other non-traditional techniques for model construction, and able to leverage and work with skills of highly experienced data scientists.
- Experience in a wide range of numerical and statistical modeling, including pattern recognition, machine learning, and NLP.
- Experience (or keen desire for experience) in a small, fast-moving, high-growth company.
- Any level of experience with Spanish.