FinOS Technology

The Financial Operating System

HEAD OF DATA SCIENCE

Login to view salary

3 days ago

Apply Now Apply Without CV

Job Description

FinOS is the definitive platform for financial services that powers digital financial products & services across Southeast Asia. We pave the way to provide financial support to the unbanked through simple, affordable and tech-enabled financial products & services.

FinOS’ Data Science team works on some of the most challenging and fascinating problems in financial industry. We foster a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to explore and innovate. If you have a strong passion for data science and machine learning, excited to develop complex machine learning models and feel strongly about communicating effectively with product owners, come talk to us! 

Job Responsibilities

  •  Drive overall data strategy
  • Lead team of data scientist, data engineer and BI analyst to innovate data science products according to market needs and build upon the current credit and lead scoring models
  • Lead partnership discussions to understand their data landscape and how we can best leverage our partnership; manage these relationships and run successful pilots that lead to Lead on data sharing negotiations and implementation
  • Work with product owners and business development team to define hypotheses, develop and execute necessary tests, experiments, and analyses to prove or disprove them
  • Translate data speak to human speak by effectively conceptualizing analysis to team members and business stakeholders
  • Drive adoption of data tools and dashboards and data driven decisions with emphasis on product analytics
  • Developing team members in the area of career development, technical knowledge and soft skills under your care.
  • Establish data policies, standards and organization
  • Work with the legal and compliance and finance teams to ensure regulatory compliance

Job Requirements

Basic Qualifications:

  • Bachelor’s and/or advanced degree in Computer Science, Data Science, Engineering, Mathematics, Informatics, Information Systems, or other related fields
  • Understanding of machine learning, deep learning, data mining, algorithmic foundations of optimization 
  • Proven track record in data management, leadership and information technology systems and tools
  • 2+ years of experience in leading a team; 5+ years of experience in application of data science and machine learning
  • Proven experience in writing and speaking about complex technical concepts to broad audiences in a simplified format
  • Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
  • Experience with machine learning framework (scikit-learn, Spark MLlib etc)
  • Proficient in one or more of the following programming languages: Python, R, Scala
  • Experience in building ML models at scale, using real-time big data pipelines on platforms such as Spark/MapReduce
  • Familiar with noSQL, postGIS, stream processing and distributed computing platforms
  • Self-motivated, independent learner, and willing to share knowledge with team members
  • Detail-oriented and efficient time manager in a dynamic and dynamic working environment
  • Strong written and verbal communication skills, with a track record of presenting to senior management

Preferred Qualifications

  • Working experience in the financial industry
  • Experience working within a high-growth, technology company is highly beneficial
  • Experience working on AWS is a big plus

We did not engage any Recruitment agencies to work on this role, please speak to our internal HR team directly.

Location

Quận 1, Hồ Chí Minh - Quận Nam Từ Liêm, Hà Nội

Level

Nhân viên

Year of Experience

5 năm

Job Type

Benefits

13rd month salary

Health insurance

Full government insurance

15 AL, 30 sick leaves and more to come

Travelling experience

Talented team members

Working: Monday - Friday