Job title: Data Scientist (Fintech)
Job type: Permanent
Emp type: Full-time
Industry: Financial Services
Expertise: Banking & Finance
Skills: Data Scientist Fintech Payments SINGAPORE
Salary type: Annual
Salary: Negotiable
Location: Singapore
Job published: 01/08/2019
Job ID: 32073
Contact name: Darren Hutchinson-Hill
Contact email: darrenh@glenhill-group.com

Job Description

 

DATA SCIENTIST (Singapore)

 

My client are one Southeast Asias fastest growing Fintech companies who are driven by a vision of a world where everyone has access to financial services. Customers have access to a mobile wallet and services such as remittances, mobile air-time and bill payments. They aim to improve people's everyday lives through convenient, accessible, and approachable financial services. Providing users with a stellar product and excellent customer experience is at the heart and soul of the business. 

 

As a fast-paced growing company they look to hire passionate, motivated professionals in improving products and accelerating financial inclusion in Southeast Asia. Great value is placed on open communication, work ownership, and continuous learning on the job.

 

Who you Are

We are looking for a highly enthusiastic Data Scientist to join a growing data team. You will be responsible for the development, maintenance and continuous improvement of machine learning models. We actively seek individuals who are high in industriousness and high in orderliness, with an intrinsic interest in the design and evaluation of field experiments at scale. The ideal candidate works well without supervision and is capable of both having independent thoughts and acting on them. 

 

Responsibilities

Work closely with data engineering team on delivering Machine Learning applications in production, and evaluating them.

 

Required skills

  • Advanced data manipulation and data visualization skills in either R or Python
  • SQL
  • Exploratory Data Analysis (EDA)
  • Understanding of probability and statistics
  • Reports in either Rmarkdown or Jupyter Notebooks
  • Causal inference
  • Feature construction for supervised learning projects
  • Ability to explain representation decisions, optimization decisions and evaluation decisions in ML projects
  • Domain knowledge in at least one functional business area (e.g. marketing, finance, operations etc)
  • Strong knowledge of data-science tools and libraries in either:
  1. R (dplyr, tidyr, ggplot2, caret, glmnet) or
  2. Python (scikit-learn, numpy, pandas, seaborn etc.)

 

Skills good to have

  • Understanding of transfer learning, unsupervised learning, text-mining
  • Understanding of the difference between competition ML and production ML
  • Understanding of business intelligence
  • Understanding of data intensive applications in general
  • Experience using data processing engines (Spark/Flink/KSQL)
  • Understanding of ML tools such as Tensorflow, Keras, xgboost
  • Managed services on the cloud (AWS, GCP, Azure etc)
  • Docker, Kubernetes
  • Knowledge of Linux and command line tools
  • CI/CD

 

Our work environment

  • Remote friendly
  • Flexible schedule
  • International geo distributed team
  • Infrequent business trips to SEA countries
  • AWS
  • Databricks Spark
  • Flexible Vacation