Data Scientists

The Data Scientist is responsible for providing expertise in applying strong data and development acumen to lead and perform a variety of roles in the creation and maintenance of data and analytical systems; step-based processes for collecting and analyzing data; and continual improvement approaches for data integrity and quality.

Location: Bonifacio Global City, Taguig City

Status: Active

# of Positions Available: 2

Job Description

 

  • Solutioning, engineering, and machine learning to develop and support cloud-based AI applications and tools utilizing cutting-edge open-source and cloud technologies. This position leads and collaborates closely with quantitative analysts to understand their analytical projects and participates in all phases of the project lifecycle, including research, requirements gathering, database development, cloud-based application development, analytical report creation.
  • This role also requires the ability to explain and defend potential conclusions drawn from data, as well as the ability to identify and investigate potential data anomalies to determine root cause and recommend corrective action.
  • Display and visualize processed information so its value can be understood. Extract information from large datasets and present something of value to clients.
  • Apply exploratory or predictive analytics to solve business problems.
  • Performs data modeling. Implement and test data modeling designs. Use advanced math and statistics expertise using massive (beyond 500GB) of data. Use modern data analytical techniques working with information retrieval, machine learning, matrix and graph algorithms, unsupervised clustering & data mining to solve business problems.
  • Applies advanced analytics, predictive modeling, and data visualization skills to different business situations.
  • Ability to work with big datasets with minimal engineering support. Demonstrate analytical and problem-solving skills, particularly those that apply to a Big Data environment.
  • Ability to integrate research and best practices into problem avoidance and continuous improvement. Exercise independent judgment in methods, techniques, and evaluation criteria for obtaining results.
  • Other job-related activities that may be assigned from time to time.
Job Qualifications/Requirements

 

Education

  • At least graduate with a Bachelor’s Degree of Computer Science/Engineering (Computer/Telecommunication)/Information Technology/Management Information System or any related course.

Related Work Experience

  • At least 5+ years working with statistics Natural Language Processing: the interactions between computers and humans

Knowledge

  • In-depth knowledge in the following:
    • Machine learning: using computers to improve as well as develop algorithms
    • Conceptual modeling: to be able to share and articulate modeling
    • Statistical analysis: to understand and work around possible limitations in models
    • Predictive modeling: most of the big data problems are towards being able to predict future outcomes
    • Nice to have: Passed AWS Certified – Big Data (Specialty) or Machine Learning certifications

Skills:

  • Must have expertise in machine learning and data analysis
  • Must have the ability to communicate technical to non-technical audiences.
  • Must have exceptional analytical, conceptual, and problem-solving abilities with a results-focused mindset
  • Must be flexible and can successfully navigate ambiguity and succeed in a fast-paced organization.
  • Must have excellent written and oral communication/presentation skills to present facts and provide recommendations
  • Must have a strong interest in/understanding of governance industry trends, challenges, opportunities.
  • Must have the ability to translate business requirements into critical data dependencies and requirements
  • Ability to lead a small team and/or project.
  • Ability to work independently with minimum supervision and with a cross-functional team.
  • Must be adept to work in a fast-paced environment with tight SLAs.
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