Selecting features, building, and optimizing classifiers using machine learning techniques
Data mining and experimental analysis using state-of-the-art methods
Processing, cleansing, and verifying the integrity of data used for analysis and training/inference
Collect/understand business requirements with varying degree of crispness
Define and design data science techniques and pipelines that address specific business problems
Work with datasets of varying degrees of size and complexity including both structured and unstructured data.
Developing pipelines to process massive data-streams in distributed computing environments such as spark, kubernetes/docker microservices
Develop proprietary algorithms to build customized solutions that go beyond standard industry tools and lead to innovative solutions.
Develop sophisticated visualization of analysis output for business users.
Provide control/analytics for all output produced to monitor/ensure established indicators/targets are met both during initial development and on an ongoing basis.
Identify opportunities for continuous improvement of current algorithms, solutions, and methodologies employed
Proactively collaborate with business partners to monitor solution health and changing requirements and develop actionable plans to address the same while optimizing for quality, use, cost, time-to-market amongst other variables.