Job Purpose: 

To develop data-driven use cases and provide actionable intelligence using advanced data analytics tools and methodologies to support the organization in achieving digitization goals, strategic and tactical decision-making by acquiring, transforming, and modeling data.

The Job:

• Analyze large and complex datasets to uncover actionable business insights.
• Develop statistical, machine learning (supervised/unsupervised), and AI models as POC and production-ready using open-source (R/Python) technologies.
• Conduct Exploratory Data Analytics, hypothesis testing, and other statistical techniques to identify important features for modeling.
• Monitor, evaluate, and optimize model performance and business outcomes.
• Define and set up performance tracking metrics.
• Execute analytics-driven campaigns and measure ROI and effectiveness.
• Collaborate with cross-functional teams to identify and develop data-driven use cases.
• Present findings and actionable intelligence to stakeholders and management.
• Maintain documentation and version control.
• Collaborate with MLOps/DevOps team to automate and deploy models in production.
• Provide L3 support for model/solution maintenance.
• Research emerging technologies, machine learning techniques, and industry best practices.
• Maintain up-to-date knowledge on new technologies/best practices.

The Person:

• Bachelor's Degree in Data Science, Artificial Intelligence, Computer Science, Statistics, Mathematics, Software Engineering, Economics, or a related field.
• 1+ years of experience in Data Science.
• Excellent understanding of machine learning techniques and algorithms.
• Hands-on experience with toolkits (R/Python or any other equivalent).
• Data visualization and communication skills.
• Score 70%+ on the Data Scientist entry exam (External hires).
• Experience in data engineering in different environments (data warehouse/big data/cloud storage).
• Continuous learner actively seeking to update knowledge.