Data Scientist

  • Lenddo
  • Jakarta, Indonesia
  • Feb 07, 2019
Full time Data Risk

Job Description

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.


The role:

  • 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 

Specific responsibilities                                                      

  • 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.                                                           

Preferred Qualifications:                                                                                                    

  • 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.


Preferred Qualifications:

  • 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.