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Data Scientist

Read straight from OpenNet's careers page, verified 19h ago.Seekless can tailor your résumé to it.
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Before you apply
LocationTaiwan
Work modehybrid
Typefull-time
SeniorityMid
Experience2+ yrs
DepartmentON BI / AI
Company size51–200 people
PostedMay 19, 2026 · 5mo ago
Verified live19h ago
At a glanceSummarised by Seekless from the posting.
Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models
2+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role
Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering
Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods
Experience with statistical and machine learning models, such as regression-based models (e.g., logistic)
Skills
MySQL
Python
AirFlow
AWS
Metabase
Redshift
Linux
Benefits
Flexible work hours
Hybrid work
Health checkups
Gym subsidy
Massages
Learning development allowance
Team lunches
Employee clubs
Maternity leave
Paternity leave
Company retreat
Health insurance
About OpenNet
OpenNet is a fast-growing technology company with products reaching 20+ countries worldwide.
We bring together talented people who enjoy solving challenges, moving fast, and learning from one another. We value collaboration, flexibility, growth, and work-life balance — creating an environment where people can do great work and enjoy the journey along the way.
What you’ll be doing
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Utilize advanced algorithms and data mining techniques to build personalized recommendation systems, optimizing product and service recommendations to enhance user experience and improve business conversion rates.
•
Conduct precise analysis of probability distributions in casino games, develop and validate mathematical models to ensure game fairness and risk control, supporting compliance operations and decision-making.
•
Continuously explore and implement various applications of LLMs in business, from natural language processing to intelligent customer service and content generation, driving enterprises toward intelligent transformation.
•
Work closely with various business units, leveraging data analysis and visualization tools to promote a data-driven decision-making culture, helping departments uncover insights from data and develop effective strategies.
Our Stack
•
MySQL (Must)
•
Python (Good to have)
•
AirFlow (Good to have)
•
AWS (Good to have)
•
Metabase (Good to have)
•
Redshift (Good to have)
•
Linux (Good to have)
Requirement
•
Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models
•
2+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role
•
Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering
•
Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods
•
Experience with statistical and machine learning models, such as regression-based models (e.g., logistic)
Benefits
We Care More About How You Work and Live
Some things are simply essential: MacBook Pro, large monitor, Sony noise-cancelling headphones, snacks, coffee and fresh fruit.Some rewards are simply standard: holiday bonuses, , quarterly performance bonuses, and referral bonuses.
But what matters even more to us:
•
Flexible work hours & hybrid work
•
Annual health check-ups, gym subsidy & monthly massages
•
A nap room — because proper rest matters
•
Learning & development allowance
•
Team lunches, employee clubs & activities
•
12 weeks maternity leave & 14 days prenatal and paternity leave
•
Annual Company Retreat — from Dubai and Phuket to Bali, Vietnam and Cebu
•
Fully covered employee portion of Labor & National Health Insurance
•
Enterprise AI tools, including ChatGPT
Great work matters. So does having a life outside of it. If that sounds like your kind of workplace, we’d love to meet you.