Data Scientist

Permanent Employee, Full-time, Remote, PST Shift
Salary: ₱120,000 to ₱140,000

Job Summary:

We are seeking a highly skilled Data Scientist to lead data-driven decision-making and develop predictive models that optimize business operations. This role requires expertise in SQL, Python, machine learning, and data visualization tools to uncover insights, drive strategic initiatives, and enhance analytical capabilities. The ideal candidate is a proactive problem-solver with a strong background in analytics, a passion for innovation, and experience in the fashion or e-commerce industry.

Responsibilities:

  • Lead data collection and integration from multiple sources, ensuring data quality and reliability.

  • Conduct advanced exploratory data analysis to uncover insights, trends, and opportunities.

  • Develop and deploy predictive models, machine learning algorithms, and statistical techniques to support business strategy.

  • Create dynamic dashboards and visualizations to communicate complex findings to senior stakeholders.

  • Manage end-to-end analytical projects, translating data insights into actionable recommendations.

  • Collaborate with technical and non-technical teams to implement data-driven solutions.

  • Stay ahead of industry trends by researching and integrating cutting-edge methodologies and technologies into analytics processes.

Requirements:

  • 5+ years of experience in data science, analytics, or a related field.

  • Expert proficiency in SQL and Python, with a track record of developing robust data solutions and models.

  • Strong experience with data visualization and BI tools (e.g., Looker, Tableau).

  • Deep understanding of statistical methods, predictive modeling, and machine learning applications.

  • Proven ability to independently drive analytical projects from concept to execution.

  • Strong problem-solving skills, with the ability to translate data insights into strategic business decisions.

  • Excellent communication and presentation skills for both technical and non-technical audiences.

  • Passion and experience in the fashion industry or e-commerce space (preferred).