Data Science Engineer

About Us:

With a legacy of over 30 years, Inspirisys has excelled in driving digital transformation through cutting-edge technologies and as a subsidiary of CAC Holdings Corporation Japan, we embrace the core tenets of Japanese work culture, prioritizing quality and attention to detail to ensure our solutions meet the highest standards. This expertise has solidified our position as a trusted partner for industry-leading OEMs in the digital age. We specialize in custom-tailored solutions in Infrastructure, Enterprise Security & Risk Services, Cloud, Banking and Product Engineering & Development, empowering clients to meet their digital objectives.

Requirements / Responsibilities:
•    Should have 3 years of experience as a Data Science Engineer
•    Focus on customer requirement and implementation
•    Usage of  open source stack apps  & frameworks
•    Building Analytics Engines and models
•    Solution execution support
•    Should have intermediate/advanced knowledge about cloud services, market segments, and customer base and industry verticals.
•    Demonstrated experience in leading or developing high quality, enterprise scale software products using a structured system development life cycle.
•    Setting up DevOps for an analytical solution
•    Exploring an extensive dataset and building new understandings using Python
•    Apply design and data analysis techniques to organize the presentation of data in visually innovative ways in order to make it easier to understand, insightful, and actionable by end users.
•    Presentation skills with a high degree of comfort with both large and small audiences.
•    Apply knowledge of ML, statistics, programming and advanced mathematics to recognize patterns & identify new opportunities for prototype building.
•    Design, develop, and evaluate predictive ML/AI models that are on par with industry standards & define metrics that measure success & customer value delivery
•    Work with engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation of the same.
•    Research, Recommend and implement best practices of machine learning systems that can scale.
•    Stay current with the recent advancements in ML/AI industry like tensor flow & actively prototype with these open-source frameworks.
•    Work closely with management to prioritize business and information needs
•    Locate and define new process improvement opportunities