Senior Data Scientist – Machine Learning

1 day ago


Pasig, National Capital Region, Philippines beBeeMachineLearning Full time $80,000 - $125,000
Crypto Data Science Role

As a senior data scientist, you will play a key role in our organization's efforts to drive business growth through data-driven decision making. The ideal candidate will have a strong foundation in machine learning and data science, with experience in optimizing ML systems and enhancing predictive model accuracy.

Key Responsibilities
  • Evaluate existing ML processes and perform statistical analysis to resolve dataset problems, ensuring high-quality data is used for informed decision making.
  • Design and implement ML systems to automate predictive models, streamlining workflows and improving efficiency.
  • Transform data science prototypes into scalable ML solutions, driving business impact through data-driven insights.
  • Solve complex problems with multi-layered datasets, leveraging expertise in machine learning and data science to deliver innovative solutions.
  • Optimize existing ML libraries and frameworks, ensuring they meet the evolving needs of the business.
  • Develop ML algorithms to analyze large volumes of historical data, providing valuable insights for strategic planning.
  • Stress test and interpret results for various market conditions, ensuring our organization remains competitive in a rapidly changing environment.
Required Skills and Qualifications
  • Bachelor's degree in computer science, data science, mathematics, or related field, demonstrating a strong foundation in mathematical and computational techniques.
  • Master's degree in computational linguistics, data science, data analytics, or similar advantageous, highlighting advanced knowledge in ML frameworks and data modeling.
  • At least two years' experience as a machine learning engineer, showcasing expertise in designing and implementing ML systems.
  • Advanced proficiency in Python, Java, R code, and relevant data structures, ensuring seamless integration with existing infrastructure.
  • Extensive knowledge of ML frameworks, libraries, data structures, data modeling, software architecture, and mathematics, statistics, algorithms, and their applications.
  • In-depth knowledge of analytical and problem-solving abilities, communication, collaboration, time management, and organizational skills, all essential for delivering high-quality results under tight deadlines.


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