Chief Data Innovator

4 days ago

Makati City, National Capital Region, Philippines beBeeData Full time

Empower business growth through data-driven innovation as a Lead Data Scientist.

This role presents an exceptional opportunity to join a fast-paced start-up environment and grow your career while driving change in the field of data science and artificial intelligence.

Key Responsibilities
  • Collaborate with stakeholders and clients to identify opportunities for leveraging company data to drive business solutions.
  • Unlock valuable insights from company databases by mining and analyzing data to enhance product development, marketing techniques, and business strategies.
  • Evaluate the effectiveness and accuracy of new data sources and data gathering techniques to optimize decision-making.
  • Design and develop custom data models and algorithms for complex data sets to inform business outcomes.
  • Apply predictive modeling to improve customer experiences, revenue, ad targeting, and other key performance indicators.
  • Coordinate with cross-functional teams to implement models and monitor outcomes, ensuring seamless integration and maximum impact.
  • Develop processes and tools to continuously monitor and analyze model performance and data accuracy, enabling data-driven decision-making.
Requirements
  • Graduate or Postgraduate degree in Computer Science, Statistics, Informatics, Information Systems, or related fields.
  • Proven knowledge of advanced statistical techniques, including regression, optimization, sentiment analysis, graph community detection, and experience applying them.
  • Expertise in statistical programming languages such as R, Python, SQL, and ability to manipulate data and extract insights from large datasets.
  • Strong problem-solving skills focused on product development and excellence in written and verbal communication.
  • A drive to learn and master new technologies and techniques, staying ahead of industry trends.
  • Experience with distributed data/compute tools like Hadoop, Kafka, Dask, Spark, and environments such as AWS, GCP, and containerization tools like Docker, Kubernetes is highly valued.
  • Proven track record of designing, planning, and implementing successful data science projects, delivering tangible results.
  • Experience with machine learning techniques, including clustering, decision trees, neural networks, and deep learning, is a significant advantage.
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