Qualification:

• Bachelor or Master’s degree DataScience/ComputerEngineering/ComputerScience/InformationTechnologyฝMathematics/Statistics or related field.

• 3-5 years of experience in data scientist, machine learning, advance data analysis, data visualization, ETL techniques, SQL, programming languages (python, R) or business intelligence.

• Working experience in model forecasting, anomaly detection, classification, computer vision or generative AI will be an advantage. Working knowledge of AWS, Azure, Alteryx, Power BI and Streamlit is an advantage.

• Proven experience in data engineering / data scientist roles.

• Proficiency in SQL and NoSQL databases.

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

• Strong programming skills in Python.

• Excellent analytical and communication skills.

Responsibilities:

• Design, build, and maintain data management systems and databases.

• Develop and optimize data pipelines and ETL processes.

• Gather, process, and analyze large-scale datasets.

• Implement tools for data quality monitoring and optimization.

• Collaborate with cross-functional teams to support data infrastructure needs.

• Create analytics tools to provide actionable insights.

• Providing business opportunities or actionable insights through data analysis and advanced modeling from complex datasets.

• Strategically designing the application of advanced analytics in business by using design thinking methodologies, insights derived from AI/ML, advanced modeling, and establishing an execution plan in alignment with key stakeholders.

• Generating initiatives or new analytical ideas to enable new business opportunities.

• Being accountable for the successful delivery of advanced model initiatives/design to development, meeting agreed quality standards and business target agreements.

• Attracting a working team to generate useful learning and insights from applying advanced analytics & modeling to drive and improve execution performance.

• Performing large-scale data analysis and developing effective machine learning or statistical models, including segmentation, classification, pattern recognition, optimization, etc., on large and complex datasets.

• Developing, building, and testing statistical and computational models that serve as key inputs for real-time contextual marketing tools.

• Communicating findings and building buy-in with key stakeholders through data visualizations.

• Interacting and collaborating with product and marketing managers to provide impactful analysis and insights aligned with business objectives.

• Working closely with other BI functions and campaign operations to provide end-to-end analytical solutions and proactively create and test decision rules for marketing campaigns.