• Develop, examine, extract, and transform data pipelines to increase efficiency, inform decision-making, and gain a competitive edge.
• Conduct descriptive analysis on data to detect data quality problems. Perform advanced statistical analysis on experimental or business data to confirm and quantify trends or patterns identified by the business.
• Create predictive/prescriptive models, algorithms, and probability engines to support data analysis or product functions.
• Support tactical decision-making by using predictive and prescriptive modeling and extracting actionable insights by identifying patterns in structured and unstructured data like images.
• Evaluate the model and algorithm effectiveness based on real-world outcomes. Design experiments and methodologies to generate and collect data for business use.
• Build, deploy, automate, and maintain advanced analytics data pipelines. Complete ad hoc analytic stakeholder requests and projects by assessing data requirements, designing analytical studies, and delivering results and recommendations.
• Design and deploy data pipeline prototypes into multiple data and analytics platforms.
• Optimize AI models for performance, scalability, and efficiency, using cloud-based resources and distributed computing frameworks.
• Build OCR models, Vision Inspection, Anomaly detection, time series forecast, NLP, Classification.
• Apply prompt engineering techniques to enhance the performance and accuracy of AI models.
• Leverage GEN AI skills to create and fine-tune AI models for various applications.
• Apply business area expertise to define and frame complex, multi-faceted projects and develop goals, direction, and work plans.
• Analyze performance data trends to identify opportunities for advanced analytics, quality improvements, and/or cost savings.
• Serve as a subject matter expert on the functionality and content of business products and tools.
• Lead, guide, train, and execute advanced analytics projects that improve business decisions.

Qualifications:

• Bachelor's Degree in Engineering, MCA, or MSc and 8+ years’ relevant experience in Data Science.
• Proficiency in programming languages including Python, R, SQL, and NoSQL.
• Experience in visualizing advanced analytics models to business insights using tools such as Power BI and Tableau.
• Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Experience in designing and deploying distributed data processing frameworks including NoSQL databases and high-performance computing clusters.
• Experience in GENAI especially prompt engineering is a plus
• A self-starter motivated to correctly interpret business needs, possessing strong problem-solving skills, as well as the technical expertise needed to perform hands-on data analysis, research, and programming work.