Data Scientist

Our Clients; Mandaluyong; On-site; PHP 700,000 - 1,200,000; Full time

Job summary

Our Clients is seeking a Data Scientist to blend analytical thinking, statistics, and programming to build reliable data and model solutions that guide business decisions and improve efficiency.

You will work with data, product, engineering, and business teams to enhance data quality, enable analytics use cases, support governance, and explore innovative enrichment and automation approaches, including Generative AI.

Qualifications

• Bachelor's or Master's degree in a quantitative field (Data Science, Statistics, Physics, Computer Science, Engineering) or equivalent.
• 2+ years of relevant data science experience in data analytics, governance, or related roles.
• Proficiency in Python and SQL, with working knowledge of Git for version control.
• Strong grasp of statistics, exploratory data analysis, and machine learning fundamentals.

Responsibilities

• Analyze complex datasets and develop reliable data and model solutions aligned with business goals.
• Perform exploratory data analysis, statistics, model development, and validation to meet needs.
• Support data governance activities including data mapping, onboarding, quality improvement, and enrichment.
• Collaborate with technical and business stakeholders to translate requirements into actionable data science solutions.
• Identify opportunities to improve operational efficiency through automation, experimentation, and Generative AI.
• Maintain data accuracy, code quality, documentation, and reproducibility.
• Identify data/model risks and communicate findings and limitations clearly.
• Contribute to knowledge sharing, data literacy, and continuous improvement across the organization.
• Manage project deliverables and coordinate with stakeholders to ensure timely completion.

Skills

Python

SQL

Git

Statistics

Machine learning

Education

Bachelor's or Master's in Data Science/Statistics/Physics/CS/Engineering

Job description

We are looking for a Data Scientist who can combine analytical thinking, statistical expertise, and programming skills to develop reliable data and model solutions that support business decisions and operational efficiency.

In this role, you will work closely with data, product, engineering, and business teams to improve data quality, enable analytics use cases, support data governance initiatives, and explore innovative approaches to data enrichment and automation.

Key Responsibilities

• Analyze complex datasets and develop reliable, business-aligned data and model solutions.
• Perform exploratory data analysis, statistical analysis, and model development and validation to address business needs.
• Support data governance activities, including data mapping, data onboarding, data quality improvement, and data enrichment.
• Collaborate with technical teams and business stakeholders to translate requirements into actionable data science solutions.
• Identify opportunities to improve operational efficiency through automation, experimentation, and emerging technologies such as Generative AI.
• Maintain high standards for data accuracy, code quality, technical documentation, and reproducibility.
• Identify potential data and model risks, recommend improvements, and communicate findings and limitations clearly.
• Contribute to knowledge-sharing initiatives, data literacy, and continuous improvement across the organization.
• Manage project deliverables, coordinate with stakeholders, and ensure timely completion of assigned initiatives.

Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Physics, Computer Science, Engineering, or a related quantitative field.
• At least 2 years of relevant experience in data science, data analytics, data governance, or related roles.
• Proficiency in Python and SQL, with working knowledge of Git for version control.
• Strong understanding of statistics, exploratory data analysis, and machine learning fundamentals.
• Experience in model development, evaluation, experimentation, and business validation.
• Ability to translate technical findings into clear, actionable business insights.
• Strong analytical, problem-solving, communication, and project management skills.
• Experience in stakeholder collaboration and cross-functional project delivery.