Data Scientist
At a glance
Mid-level Data Science role at Fuku. Taipei · full-time.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Find patterns and useful conclusions in complex datasets, then turn them into recommendations
- Build machine learning approaches to address business problems and improve their performance for production use
- Work with other teams to convert business goals into data-based solutions
- Create and maintain workflows for collecting, processing and analyzing data at scale
- Present findings through clear charts and reports while safeguarding data quality and security
What you bring
- A degree in data science, computer science, statistics or a related discipline
- Hands-on data scientist experience or similar work, supported by a strong project portfolio
- You can program in Python, R or SQL and use machine learning libraries such as TensorFlow or another listed option
- You understand statistical analysis, data modeling and predictive analytics, and can explain technical findings clearly
Who this fits
This mid-level, full-time role is based onsite in Taipei, Taiwan. It suits someone comfortable working independently and with cross-functional teams, and presenting technical ideas to non-technical stakeholders.
From the employer
About the company:
Hytech is a leading technology solutions provider specializing in innovative data-driven strategies to empower businesses across various industries. With a commitment to excellence and a culture of collaboration, Hytech leverages cutting-edge technologies to deliver impactful solutions. Our team is dedicated to fostering growth, innovation, and success for our clients and employees alike.
Job responsibilities:
- Analyze large and complex datasets to identify trends, patterns, and actionable insights.
- Develop and implement machine learning models and algorithms to solve business challenges.
- Collaborate with cross-functional teams to understand business objectives and translate them into data-driven solutions.
- Design and maintain scalable data pipelines and workflows for data collection, processing, and analysis.
- Communicate findings and recommendations to stakeholders through clear visualizations and reports.
- Stay updated on the latest advancements in data science, machine learning, and AI technologies.
- Ensure data quality, integrity, and security throughout the data lifecycle.
- Optimize and fine-tune models for performance and scalability in production environments.
Job requirements:
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
- Proven experience as a Data Scientist or in a similar role, with a strong portfolio of projects.
- Proficiency in programming languages such as Python, R, or SQL.
- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong knowledge of statistical analysis, data modeling, and predictive analytics.
- Familiarity with data visualization tools such as Tableau, Power BI, or Matplotlib.
- Experience working with big data technologies (e.g., Hadoop, Spark) is a plus.
- Excellent problem-solving skills and the ability to work independently or in a team environment.
- Strong communication skills to effectively present technical concepts to non-technical stakeholders.
Job benefits:
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance plans.
- Flexible work hours and remote work options.
- Generous paid time off, including vacation, sick leave, and holidays.
- Professional development opportunities, including training programs and certifications.
- Access to cutting-edge tools and technologies.
- Collaborative and inclusive work environment.
- Employee wellness programs and resources.
- Opportunities for career growth and advancement within the company.
Data Science work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Science
Find me workBy the team behind dataroles.