Data Scientist
2 months ago
Key Responsibilities:
Collaborate with stakeholders to plan, design, develop, test, and maintain the digital data center and analytics initiative.Identify areas and metrics to apply optimization or predictive analytics in the Business and create a charter for deploying machine learning models. Document the technology requirements and build use cases using the appropriate algorithms for the business functions and enable their deployment for go-live. Clearly communicate processes, potential solutions, and use-cases through documentation, wireframes, interaction flows, prototypes, and visuals.Drive the implementation, testing, evolution, and maintenance of the various machine learning models developed. Be able to collect and provide relevant domain as well technical insights to fine-tune the Data Analytics Models built and improve the accuracy and usability of outputs generated. Take over model maintenance of models already deployed. Should have experience in ML Ops.Work to understand and challenge solutions proposed by analytics partners. Be responsible for the quality and timely delivery of solutions delivered to the Business.Work with business or functions in designing front-end business intelligence multi-dimensional Power BI dashboards effectively.
Educational Qualification:
Graduate/Post Graduate degree in Computer Science, Statistics, Data Science, or a related field.
Experience:• At least 4-6 years of experience in delivering large enterprise Analytics projects.• Overall experience of 7 - 8 years in Enterprise IT.
The Industry to be hired from:• Chemical/Pharma/FMCG• Manufacturing IT• Big 4, IT/ITES Organizations
Skills:• Proven experience as an Analytics Manager or Data Engineer/Scientist.• Solid experience in data analysis, data engineering, data science – modeling and optimization, cloud computing architecture, and big data management and reporting; industry experience is a plus.• Knowledge of Excel, Python/R, and SQL.• Familiarity with business intelligence tools/data Visualization tools - Power BI.• Demonstrates an understanding of the IT environment as a whole, including enterprise applications like HRMS, ERPs, CRM, etc.
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