Job Summary

Global MNC Tech is seeking a highly analytical and innovative Data Scientist to join our Remote Predictive Analytics team supporting our Retail Hub initiatives. In this role, you will leverage advanced statistical methods, machine learning models, and data-driven insights to optimize retail performance, enhance customer experience, and drive strategic decision-making. The ideal candidate is passionate about transforming complex datasets into actionable business intelligence and thrives in a fast-paced, collaborative environment.

Key Responsibilities

• Develop, validate, and deploy predictive models to support retail forecasting, demand planning, and customer behavior analysis.

• Analyze large, complex datasets to uncover trends, patterns, and actionable insights.

• Collaborate with cross-functional teams including Product, Marketing, Supply Chain, and Engineering to translate business needs into data solutions.

• Design and implement A/B tests and experiments to evaluate business strategies.

• Build and maintain scalable data pipelines and machine learning workflows.

• Present findings and recommendations to stakeholders through clear visualizations and reports.

• Continuously monitor model performance and improve accuracy and efficiency.

• Stay current with emerging trends in data science, AI, and retail analytics.

Required Skills and Qualifications

• Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

• Strong proficiency in Python or R for data analysis and modeling.

• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

• Solid knowledge of SQL and experience working with large-scale databases.

• Expertise in statistical analysis, predictive modeling, and data mining techniques.

• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib.

• Strong problem-solving skills and attention to detail.

• Excellent written and verbal communication skills in English.

Experience

• 3–6 years of professional experience in data science or predictive analytics.

• Proven experience in retail, e-commerce, or consumer analytics is strongly preferred.

• Demonstrated success in deploying machine learning models into production environments.

• Experience working in remote or distributed teams is a plus.

Working Hours

• Fully remote role with flexible working hours.

• Must be available for core collaboration hours aligned with global team time zones.

• Occasional extended hours may be required during critical project phases.

Knowledge, Skills, and Abilities

• Strong business acumen with the ability to connect data insights to retail outcomes.

• Ability to manage multiple projects and priorities simultaneously.

• High level of curiosity and commitment to continuous learning.

• Strong collaboration and stakeholder management skills.

• Ability to work independently in a remote environment.

• Familiarity with cloud platforms (AWS, Azure, or GCP) is advantageous.

• Understanding of MLOps practices and model lifecycle management is a plus.

Benefits

• Competitive salary and performance-based incentives.

• Flexible remote work environment.

• Health and wellness benefits package.

• Professional development and certification support.

• Paid time off and global holiday observance.

• Access to cutting-edge tools and technologies.

• Inclusive and collaborative company culture.

Why Join

At Global MNC Tech, we empower data-driven innovation at scale. You will work on impactful retail analytics projects that directly influence business growth and customer experience worldwide. We foster a culture of curiosity, ownership, and continuous improvement while providing the flexibility of remote work and the stability of a global organization. If you are passionate about predictive analytics and want to make a measurable impact, this is the opportunity for you.

How to Apply

Interested candidates should submit their updated resume along with a brief cover letter highlighting relevant predictive analytics and retail experience. Qualified applicants will be contacted for the next steps in the selection process.